From ba1a4b63c52905ef23263d6f0dd2be35ea00d122 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 30 Jan 2023 11:45:35 +0100 Subject: [PATCH 01/70] feat: add tensorflow tensor Signed-off-by: anna-charlotte --- docarray/typing/__init__.py | 2 + docarray/typing/tensor/__init__.py | 2 + docarray/typing/tensor/tensorflow_tensor.py | 141 ++++++++++++++++++++ 3 files changed, 145 insertions(+) create mode 100644 docarray/typing/tensor/tensorflow_tensor.py diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index c1aac2b1f1f..8bf129f43d1 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -5,6 +5,7 @@ from docarray.typing.tensor.embedding.embedding import AnyEmbedding, NdArrayEmbedding from docarray.typing.tensor.ndarray import NdArray from docarray.typing.tensor.tensor import AnyTensor +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor from docarray.typing.tensor.video import VideoNdArray from docarray.typing.url import ( AnyUrl, @@ -31,6 +32,7 @@ 'AnyUrl', 'ID', 'AnyTensor', + 'TensorFlowTensor', 'NdArrayEmbedding', 'ImageBytes', 'ImageTensor', diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index 98b99eff92b..79b3a3371a5 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -2,6 +2,7 @@ from docarray.typing.tensor.image import ImageNdArray, ImageTensor from docarray.typing.tensor.ndarray import NdArray from docarray.typing.tensor.tensor import AnyTensor +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor __all__ = [ 'NdArray', @@ -10,6 +11,7 @@ 'NdArrayEmbedding', 'ImageNdArray', 'ImageTensor', + 'TensorFlowTensor', ] try: diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py new file mode 100644 index 00000000000..2076a83ca83 --- /dev/null +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -0,0 +1,141 @@ +from typing import TYPE_CHECKING, Any, Dict, Generic, Type, TypeVar, Union + +import numpy as np +import tensorflow as tf + +from docarray.typing.proto_register import _register_proto +from docarray.typing.tensor.abstract_tensor import AbstractTensor + +if TYPE_CHECKING: + from pydantic.fields import ModelField + from pydantic import BaseConfig + from docarray.proto import NdArrayProto + from docarray.computation.tensorflow_backend import TensorFlowCompBackend + +from docarray.base_document.base_node import BaseNode + +T = TypeVar('T', bound='TensorFlowTensor') +ShapeT = TypeVar('ShapeT') + +tf_base: type = type(tf.Tensor) +node_base: type = type(BaseNode) + + +class metaTensorFlow( + AbstractTensor.__parametrized_meta__, # type: ignore + node_base, # type: ignore + tf_base, # type: ignore +): # type: ignore + pass + + +@_register_proto(proto_type_name='tensorflow_tensor') +class TensorFlowTensor(AbstractTensor, Generic[ShapeT], metaclass=metaTensorFlow): + + __parametrized_meta__ = metaTensorFlow + + def __init__(self, tensor: tf.Tensor): + super().__init__() + self._tensor = tensor + + @property + def tensor(self): + return self._tensor + + @classmethod + def __get_validators__(cls): + # one or more validators may be yielded which will be called in the + # order to validate the input, each validator will receive as an input + # the value returned from the previous validator + yield cls.validate + + @classmethod + def validate( + cls: Type[T], + value: Union[T, np.ndarray, Any], + field: 'ModelField', + config: 'BaseConfig', + ) -> T: + if isinstance(value, tf.Tensor): + return cls(tensor=value) + else: + try: + arr: tf.Tensor = tf.constant(value) + return cls(tensor=arr) + except Exception: + pass # handled below + raise ValueError( + f'Expected a tensorflow.Tensor compatible type, got {type(value)}' + ) + + @classmethod + def _docarray_from_native(cls: Type[T], value: tf.Tensor) -> T: + """Create a TensorFlowTensor from a native tensorflow.Tensor + + :param value: the native tf.Tensor + :return: a TensorFlowTensor + """ + if cls.__unparametrizedcls__: # This is not None if the tensor is parametrized + cls_param = cls.__unparametrizedcls__ + else: + cls_param = cls + return cls_param(tensor=value) + + @staticmethod + def get_comp_backend() -> 'TensorFlowCompBackend': + """Return the computational backend of the tensor""" + from docarray.computation.tensorflow_backend import TensorFlowCompBackend + + return TensorFlowCompBackend() + + @classmethod + def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None: + # this is needed to dump to json + field_schema.update(type='string', format='tensor') + + def _docarray_to_json_compatible(self) -> np.ndarray: + """ + Convert TensorFlowTensor into a json compatible object + :return: a representation of the tensor compatible with orjson + """ + return self.unwrap().numpy() + + def to_protobuf(self) -> 'NdArrayProto': + pass + + @classmethod + def from_protobuf(cls: Type[T], pb_msg: 'NdArrayProto') -> 'T': + pass + + @classmethod + def from_ndarray(cls: Type[T], value: np.ndarray) -> T: + """Create a TensorFlowTensor from a numpy array. + + :param value: the numpy array + :return: a TensorFlowTensor + """ + return cls._docarray_from_native(tf.convert_to_tensor(value)) + + def unwrap(self): + """ + Return the original tensorflow.Tensor without any memory copy. + + The original view rest intact and is still a Document TensorFlowTensor + but the return object is a pure tf.Tensor but both object share + the same memory layout. + + EXAMPLE USAGE + .. code-block:: python + from docarray.typing import TensorFlowTensor + import tensorflow as tf + + t1 = TensorFlowTensor.validate(tf.zeros((3, 224, 224)), None, None) + # here t1 is a docarray TensorFlowTensor + t2 = t.unwrap() + # here t2 is a pure tf.Tensor but t1 is still a Docarray TensorFlowTensor + # But both share the same underlying memory + + + :return: a tf.Tensor + """ + return self.tensor From 978dfe4dd9672c8d9fc39663bc8213effc9463ef Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 30 Jan 2023 16:13:12 +0100 Subject: [PATCH 02/70] feat: wip add tf comp backend Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 92 +++++++++++++ docarray/typing/tensor/ndarray.py | 2 +- docarray/typing/tensor/tensorflow_tensor.py | 6 +- docarray/typing/tensor/torch_tensor.py | 2 +- .../tensorflow_backend/__init__.py | 0 .../tensorflow_backend/test_basics.py | 123 ++++++++++++++++++ .../tensorflow_backend/test_metrics.py | 0 .../tensorflow_backend/test_retrieval.py | 0 8 files changed, 218 insertions(+), 7 deletions(-) create mode 100644 docarray/computation/tensorflow_backend.py create mode 100644 tests/units/computation_backends/tensorflow_backend/__init__.py create mode 100644 tests/units/computation_backends/tensorflow_backend/test_basics.py create mode 100644 tests/units/computation_backends/tensorflow_backend/test_metrics.py create mode 100644 tests/units/computation_backends/tensorflow_backend/test_retrieval.py diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py new file mode 100644 index 00000000000..ff51b3cfc23 --- /dev/null +++ b/docarray/computation/tensorflow_backend.py @@ -0,0 +1,92 @@ +import typing +from typing import Any, List, Optional, Tuple, Union + +import numpy as np +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp + +from docarray.computation import AbstractComputationalBackend +from docarray.computation.numpy_backend import NumpyCompBackend + + +class TensorFlowCompBackend(NumpyCompBackend, AbstractComputationalBackend[tf.Tensor]): + """ + Computational backend for TensorFlow. + """ + + @staticmethod + def stack( + tensors: Union[List['tf.Tensor'], Tuple['tf.Tensor']], dim: int = 0 + ) -> 'tf.Tensor': + return tnp.stack(tensors, axis=dim) + + @staticmethod + def n_dim(array: 'tf.Tensor') -> int: + return tnp.ndim(array) + + @staticmethod + def squeeze(tensor: 'tf.Tensor') -> 'tf.Tensor': + return tnp.squeeze(tensor) + + @staticmethod + def to_numpy(array: 'tf.Tensor') -> 'np.ndarray': + return array.numpy() + + @staticmethod + def empty( + shape: Tuple[int, ...], + dtype: Optional[Any] = None, + device: Optional[Any] = None, + ) -> 'tf.Tensor': + return tnp.empty(shape=shape, dtype=dtype) + + @staticmethod + def none_value() -> typing.Any: + return tf.constant(float('nan')) + + @staticmethod + def to_device(tensor: 'tf.Tensor', device: str) -> 'tf.Tensor': + pass + + @staticmethod + def device(tensor: 'tf.Tensor') -> Optional[str]: + return tensor.device + + @staticmethod + def shape(tensor: 'tf.Tensor') -> Tuple[int, ...]: + return tuple(tnp.shape(tensor)) + + @staticmethod + def reshape(tensor: 'tf.Tensor', shape: Tuple[int, ...]) -> 'tf.Tensor': + return tf.reshape(tensor, shape) + + @staticmethod + def detach(tensor: 'tf.Tensor') -> 'tf.Tensor': + return tf.stop_gradient(tensor) + + @staticmethod + def dtype(tensor: 'tf.Tensor') -> tf.dtypes: + return tensor.dtype + + @staticmethod + def isnan(tensor: 'tf.Tensor') -> 'tf.Tensor': + return tnp.isnan(tensor) + + @staticmethod + def minmax_normalize( + tensor: 'tf.Tensor', + t_range: Tuple = (0.0, 1.0), + x_range: Optional[Tuple] = None, + eps: float = 1e-7, + ) -> 'tf.Tensor': + a, b = t_range + + t = tf.cast(tensor, tf.float32) + min_d = x_range[0] if x_range else tnp.min(t, axis=-1, keepdims=True) + max_d = x_range[1] if x_range else tnp.max(t, axis=-1, keepdims=True) + + i = (b - a) * (t - min_d) / (max_d - min_d + tf.constant(eps) + a) + print(f"i = {i}") + + normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) + return tf.cast(normalized, tensor.dtype) diff --git a/docarray/typing/tensor/ndarray.py b/docarray/typing/tensor/ndarray.py index 8e75ea72732..7c2ef023764 100644 --- a/docarray/typing/tensor/ndarray.py +++ b/docarray/typing/tensor/ndarray.py @@ -151,7 +151,7 @@ def unwrap(self) -> np.ndarray: import numpy as np t1 = NdArray.validate(np.zeros((3, 224, 224)), None, None) - # here t is a docarray TenNdArray + # here t1 is a docarray NdArray t2 = t.unwrap() # here t2 is a pure np.ndarray but t1 is still a Docarray NdArray # But both share the same underlying memory diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 2076a83ca83..a653eb3751f 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -36,11 +36,7 @@ class TensorFlowTensor(AbstractTensor, Generic[ShapeT], metaclass=metaTensorFlow def __init__(self, tensor: tf.Tensor): super().__init__() - self._tensor = tensor - - @property - def tensor(self): - return self._tensor + self.tensor = tensor @classmethod def __get_validators__(cls): diff --git a/docarray/typing/tensor/torch_tensor.py b/docarray/typing/tensor/torch_tensor.py index d33bdd9d3fe..c171024bf60 100644 --- a/docarray/typing/tensor/torch_tensor.py +++ b/docarray/typing/tensor/torch_tensor.py @@ -123,7 +123,7 @@ def _docarray_to_json_compatible(self) -> np.ndarray: Convert torchTensor into a json compatible object :return: a representation of the tensor compatible with orjson """ - return self.numpy() ## might need to check device later + return self.numpy() ## might need to check device later def unwrap(self) -> torch.Tensor: """ diff --git a/tests/units/computation_backends/tensorflow_backend/__init__.py b/tests/units/computation_backends/tensorflow_backend/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py new file mode 100644 index 00000000000..661dc50b74e --- /dev/null +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -0,0 +1,123 @@ +import numpy as np +import pytest +import tensorflow as tf + +from docarray.computation.tensorflow_backend import TensorFlowCompBackend + + +def test_to_device(): + with pytest.raises(NotImplementedError): + TensorFlowCompBackend.to_device(tf.zeros((10, 3)), 'CPU:0') + + +@pytest.mark.parametrize( + 'array,result', + [ + (tf.zeros((5)), 1), + (tf.zeros((1, 5)), 2), + (tf.zeros((5, 5)), 2), + (tf.zeros(()), 0), + ], +) +def test_n_dim(array, result): + assert TensorFlowCompBackend.n_dim(array) == result + + +@pytest.mark.parametrize( + 'array,result', + [ + (tf.zeros((10,)), (10,)), + (tf.zeros((5, 5)), (5, 5)), + (tf.zeros(()), ()), + ], +) +def test_shape(array, result): + shape = TensorFlowCompBackend.shape(array) + assert shape == result + assert type(shape) == tuple + + +# def test_device(): +# array = tf.constant([1, 2, 3]) +# assert TensorFlowCompBackend.device(array) is not None + + +@pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) +def test_dtype(dtype): + array = tf.constant([1, 2, 3], dtype=dtype) + assert TensorFlowCompBackend.dtype(array) == dtype + + +def test_empty(): + array = TensorFlowCompBackend.empty((10, 3)) + assert array.shape == (10, 3) + + +def test_empty_dtype(): + tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) + assert tensor.shape == (10, 3) + assert tensor.dtype == tf.int32 + + +# def test_empty_device(): +# with pytest.raises(NotImplementedError): +# TensorFlowCompBackend.empty((10, 3), device='CPU:0') + + +def test_squeeze(): + tensor = tf.zeros(shape=(1, 1, 3, 1)) + squeezed = TensorFlowCompBackend.squeeze(tensor) + assert squeezed.shape == (3,) + + +@pytest.mark.parametrize( + 'array,t_range,x_range,result', + [ + ( + tf.constant([0, 1, 2, 3, 4, 5]), + (0, 10), + None, + tf.constant([0, 2, 4, 6, 8, 10]), + ), + ( + tf.constant([0, 1, 2, 3, 4, 5]), + (0, 10), + (0, 10), + tf.constant([0, 1, 2, 3, 4, 5]), + ), + ( + tf.constant([[0.0, 1.0], [0.0, 1.0]]), + (0, 10), + None, + tf.constant([[0.0, 10.0], [0.0, 10.0]]), + ), + ], +) +def test_minmax_normalize(array, t_range, x_range, result): + output = TensorFlowCompBackend.minmax_normalize( + tensor=array, t_range=t_range, x_range=x_range + ) + assert np.allclose(output, result) + + +def test_reshape(): + tensor = tf.zeros((3, 224, 224)) + reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) + assert reshaped.shape == (224, 224, 3) + + +def test_stack(): + t0 = tf.zeros((3, 224, 224)) + t1 = tf.ones((3, 224, 224)) + + stacked1 = TensorFlowCompBackend.stack([t0, t1], dim=0) + from tensorflow.python.framework.ops import EagerTensor + + assert isinstance(stacked1, EagerTensor) + assert stacked1.shape == (2, 3, 224, 224) + + stacked2 = TensorFlowCompBackend.stack([t0, t1], dim=-1) + from tensorflow.python.framework.ops import EagerTensor + + assert isinstance(stacked2, EagerTensor) + assert stacked2.shape == (3, 224, 224, 2) diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py new file mode 100644 index 00000000000..e69de29bb2d From 712c950299f4ccd19b3b63b7a73d468608e4f51d Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 30 Jan 2023 17:32:19 +0100 Subject: [PATCH 03/70] fix: comp backend working of TensorFlowTensor, not tf tensor Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 58 ++++++------ .../tensorflow_backend/test_basics.py | 39 ++++---- .../typing/tensor/test_tensor_flow_tensor.py | 90 +++++++++++++++++++ 3 files changed, 140 insertions(+), 47 deletions(-) create mode 100644 tests/units/typing/tensor/test_tensor_flow_tensor.py diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index ff51b3cfc23..4eb687a7a8e 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -7,6 +7,7 @@ from docarray.computation import AbstractComputationalBackend from docarray.computation.numpy_backend import NumpyCompBackend +from docarray.typing import TensorFlowTensor class TensorFlowCompBackend(NumpyCompBackend, AbstractComputationalBackend[tf.Tensor]): @@ -16,72 +17,75 @@ class TensorFlowCompBackend(NumpyCompBackend, AbstractComputationalBackend[tf.Te @staticmethod def stack( - tensors: Union[List['tf.Tensor'], Tuple['tf.Tensor']], dim: int = 0 - ) -> 'tf.Tensor': - return tnp.stack(tensors, axis=dim) + tensors: Union[List['TensorFlowTensor'], Tuple['TensorFlowTensor']], + dim: int = 0, + ) -> 'TensorFlowTensor': + return TensorFlowTensor(tnp.stack([t.tensor for t in tensors], axis=dim)) @staticmethod - def n_dim(array: 'tf.Tensor') -> int: - return tnp.ndim(array) + def n_dim(array: 'TensorFlowTensor') -> int: + return tnp.ndim(array.tensor) @staticmethod - def squeeze(tensor: 'tf.Tensor') -> 'tf.Tensor': - return tnp.squeeze(tensor) + def squeeze(tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': + return TensorFlowTensor(tnp.squeeze(tensor.tensor)) @staticmethod - def to_numpy(array: 'tf.Tensor') -> 'np.ndarray': - return array.numpy() + def to_numpy(array: 'TensorFlowTensor') -> 'np.ndarray': + return array.tensor.numpy() @staticmethod def empty( shape: Tuple[int, ...], dtype: Optional[Any] = None, device: Optional[Any] = None, - ) -> 'tf.Tensor': - return tnp.empty(shape=shape, dtype=dtype) + ) -> 'TensorFlowTensor': + return TensorFlowTensor(tnp.empty(shape=shape, dtype=dtype)) @staticmethod def none_value() -> typing.Any: return tf.constant(float('nan')) @staticmethod - def to_device(tensor: 'tf.Tensor', device: str) -> 'tf.Tensor': + def to_device(tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor': pass @staticmethod - def device(tensor: 'tf.Tensor') -> Optional[str]: + def device(tensor: 'TensorFlowTensor') -> Optional[str]: return tensor.device @staticmethod - def shape(tensor: 'tf.Tensor') -> Tuple[int, ...]: - return tuple(tnp.shape(tensor)) + def shape(tensor: 'TensorFlowTensor') -> Tuple[int, ...]: + return tuple(tnp.shape(tensor.tensor)) @staticmethod - def reshape(tensor: 'tf.Tensor', shape: Tuple[int, ...]) -> 'tf.Tensor': - return tf.reshape(tensor, shape) + def reshape( + tensor: 'TensorFlowTensor', shape: Tuple[int, ...] + ) -> 'TensorFlowTensor': + return tf.reshape(tensor.tensor, shape) @staticmethod - def detach(tensor: 'tf.Tensor') -> 'tf.Tensor': - return tf.stop_gradient(tensor) + def detach(tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': + return TensorFlowTensor(tf.stop_gradient(tensor)) @staticmethod - def dtype(tensor: 'tf.Tensor') -> tf.dtypes: - return tensor.dtype + def dtype(tensor: 'TensorFlowTensor') -> tf.dtypes: + return tensor.tensor.dtype @staticmethod - def isnan(tensor: 'tf.Tensor') -> 'tf.Tensor': - return tnp.isnan(tensor) + def isnan(tensor: 'TensorFlowTensor') -> TensorFlowTensor: + return TensorFlowTensor(tnp.isnan(tensor.tensor)) @staticmethod def minmax_normalize( - tensor: 'tf.Tensor', + tensor: 'TensorFlowTensor', t_range: Tuple = (0.0, 1.0), x_range: Optional[Tuple] = None, eps: float = 1e-7, - ) -> 'tf.Tensor': + ) -> 'TensorFlowTensor': a, b = t_range - t = tf.cast(tensor, tf.float32) + t = tf.cast(tensor.tensor, tf.float32) min_d = x_range[0] if x_range else tnp.min(t, axis=-1, keepdims=True) max_d = x_range[1] if x_range else tnp.max(t, axis=-1, keepdims=True) @@ -89,4 +93,4 @@ def minmax_normalize( print(f"i = {i}") normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) - return tf.cast(normalized, tensor.dtype) + return tf.cast(normalized, tensor.tensor.dtype) diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 661dc50b74e..8077e175084 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -3,6 +3,7 @@ import tensorflow as tf from docarray.computation.tensorflow_backend import TensorFlowCompBackend +from docarray.typing import TensorFlowTensor def test_to_device(): @@ -20,6 +21,7 @@ def test_to_device(): ], ) def test_n_dim(array, result): + array = TensorFlowTensor(array) assert TensorFlowCompBackend.n_dim(array) == result @@ -32,6 +34,7 @@ def test_n_dim(array, result): ], ) def test_shape(array, result): + array = TensorFlowTensor(array) shape = TensorFlowCompBackend.shape(array) assert shape == result assert type(shape) == tuple @@ -44,19 +47,19 @@ def test_shape(array, result): @pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) def test_dtype(dtype): - array = tf.constant([1, 2, 3], dtype=dtype) + array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=dtype)) assert TensorFlowCompBackend.dtype(array) == dtype def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) - assert array.shape == (10, 3) + assert array.tensor.shape == (10, 3) def test_empty_dtype(): - tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) - assert tensor.shape == (10, 3) - assert tensor.dtype == tf.int32 + tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) + assert tf_tensor.tensor.shape == (10, 3) + assert tf_tensor.tensor.dtype == tf.int32 # def test_empty_device(): @@ -65,9 +68,9 @@ def test_empty_dtype(): def test_squeeze(): - tensor = tf.zeros(shape=(1, 1, 3, 1)) + tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) squeezed = TensorFlowCompBackend.squeeze(tensor) - assert squeezed.shape == (3,) + assert squeezed.tensor.shape == (3,) @pytest.mark.parametrize( @@ -95,29 +98,25 @@ def test_squeeze(): ) def test_minmax_normalize(array, t_range, x_range, result): output = TensorFlowCompBackend.minmax_normalize( - tensor=array, t_range=t_range, x_range=x_range + tensor=TensorFlowTensor(array), t_range=t_range, x_range=x_range ) assert np.allclose(output, result) def test_reshape(): - tensor = tf.zeros((3, 224, 224)) + tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) - assert reshaped.shape == (224, 224, 3) + assert reshaped.tensor.shape == (224, 224, 3) def test_stack(): - t0 = tf.zeros((3, 224, 224)) - t1 = tf.ones((3, 224, 224)) + t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) + t1 = TensorFlowTensor(tf.ones((3, 224, 224))) stacked1 = TensorFlowCompBackend.stack([t0, t1], dim=0) - from tensorflow.python.framework.ops import EagerTensor - - assert isinstance(stacked1, EagerTensor) - assert stacked1.shape == (2, 3, 224, 224) + assert isinstance(stacked1, TensorFlowTensor) + assert stacked1.tensor.shape == (2, 3, 224, 224) stacked2 = TensorFlowCompBackend.stack([t0, t1], dim=-1) - from tensorflow.python.framework.ops import EagerTensor - - assert isinstance(stacked2, EagerTensor) - assert stacked2.shape == (3, 224, 224, 2) + assert isinstance(stacked2, TensorFlowTensor) + assert stacked2.tensor.shape == (3, 224, 224, 2) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py new file mode 100644 index 00000000000..80efbbd5813 --- /dev/null +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -0,0 +1,90 @@ +import numpy as np +import pytest +import tensorflow as tf +from pydantic import schema_json_of +from pydantic.tools import parse_obj_as + +from docarray.base_document.io.json import orjson_dumps +from docarray.typing import TensorFlowTensor + + +def test_json_schema(): + schema_json_of(TensorFlowTensor) + + +def test_dump_json(): + tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) + orjson_dumps(tensor) + + +def test_unwrap(): + tf_tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) + unwrapped = tf_tensor.unwrap() + + assert not isinstance(unwrapped, TensorFlowTensor) + assert isinstance(tf_tensor, TensorFlowTensor) + assert isinstance(unwrapped, tf.Tensor) + + assert np.allclose(unwrapped, np.zeros((3, 224, 224))) + + +def test_parametrized(): + # correct shape, single axis + tf_tensor = parse_obj_as(TensorFlowTensor[128], tf.zeros(128)) + print(f"tf_tensor = {tf_tensor}") + print(f"type(tf_tensor) = {type(tf_tensor)}") + + assert isinstance(tf_tensor, TensorFlowTensor) + print(f"type(tf_tensor.tensor) = {type(tf_tensor.tensor)}") + + assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (128,) + + # correct shape, multiple axis + tf_tensor = parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((3, 224, 224))) + assert isinstance(tf_tensor, TensorFlowTensor) + assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (3, 224, 224) + + # wrong but reshapable shape + tf_tensor = parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 3, 224))) + assert isinstance(tf_tensor, TensorFlowTensor) + # assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (3, 224, 224) + + # wrong and not reshapable shape + from tensorflow.python.framework.errors_impl import InvalidArgumentError + + with pytest.raises(InvalidArgumentError): + parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 224))) + + +def test_parametrized_with_str(): + # test independent variable dimensions + tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((3, 224, 224))) + assert isinstance(tf_tensor, TensorFlowTensor) + assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (3, 224, 224) + + tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((3, 60, 128))) + assert isinstance(tf_tensor, TensorFlowTensor) + assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (3, 60, 128) + + with pytest.raises(ValueError): + parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((4, 224, 224))) + + with pytest.raises(ValueError): + parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((100, 1))) + + # test dependent variable dimensions + tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 224, 224))) + assert isinstance(tf_tensor, TensorFlowTensor) + assert isinstance(tf_tensor.tensor, tf.Tensor) + assert tf_tensor.tensor.shape == (3, 224, 224) + + with pytest.raises(ValueError): + _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60, 128))) + + with pytest.raises(ValueError): + _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60))) From fd8818572208b8e12ce353bcc6e995daa6e05dac Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 30 Jan 2023 17:33:02 +0100 Subject: [PATCH 04/70] test: remove redundant print statements Signed-off-by: anna-charlotte --- poetry.lock | 2304 ++++++++--------- .../typing/tensor/test_tensor_flow_tensor.py | 5 - 2 files changed, 1152 insertions(+), 1157 deletions(-) diff --git a/poetry.lock b/poetry.lock index 719cf8dd921..97fc74465e7 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,3 @@ -# This file is automatically @generated by Poetry and should not be 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TensorFlowTensor) - print(f"type(tf_tensor.tensor) = {type(tf_tensor.tensor)}") - assert isinstance(tf_tensor.tensor, tf.Tensor) assert tf_tensor.tensor.shape == (128,) From 17fe3d5f67a837e151015284b9aa9123471e31dc Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 09:15:05 +0100 Subject: [PATCH 05/70] feat: add comp backend retrieval Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 53 +++++++++++++++++- .../tensorflow_backend/test_retrieval.py | 55 +++++++++++++++++++ 2 files changed, 106 insertions(+), 2 deletions(-) diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 4eb687a7a8e..745f0fd83a2 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -6,11 +6,10 @@ import tensorflow._api.v2.experimental.numpy as tnp from docarray.computation import AbstractComputationalBackend -from docarray.computation.numpy_backend import NumpyCompBackend from docarray.typing import TensorFlowTensor -class TensorFlowCompBackend(NumpyCompBackend, AbstractComputationalBackend[tf.Tensor]): +class TensorFlowCompBackend(AbstractComputationalBackend[tf.Tensor]): """ Computational backend for TensorFlow. """ @@ -94,3 +93,53 @@ def minmax_normalize( normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) return tf.cast(normalized, tensor.tensor.dtype) + + class Retrieval(AbstractComputationalBackend.Retrieval[tf.Tensor]): + """ + Abstract class for retrieval and ranking functionalities + """ + + @staticmethod + def top_k( + values: 'TensorFlowTensor', + k: int, + descending: bool = False, + device: Optional[str] = None, + ) -> Tuple['tf.Tensor', 'tf.Tensor']: + """ + Retrieves the top k smallest values in `values`, + and returns them alongside their indices in the input `values`. + Can also be used to retrieve the top k largest values, + by setting the `descending` flag. + + :param values: Torch tensor of values to rank. + Should be of shape (n_queries, n_values_per_query). + Inputs of shape (n_values_per_query,) will be expanded + to (1, n_values_per_query). + :param k: number of values to retrieve + :param descending: retrieve largest values instead of smallest values + :param device: the computational device to use, + can be either `cpu` or a `cuda` device. + :return: Tuple containing the retrieved values, and their indices. + Both ar of shape (n_queries, k) + """ + values = values.tensor + if device is not None: + values = values.to(device) + if len(values.shape) <= 1: + values = tf.expand_dims(values, axis=0) + + len_values = values.shape[-1] if len(values.shape) > 1 else len(values) + k = min(k, len_values) + + if not descending: + values = -values + + result = tf.math.top_k(input=values, k=k, sorted=True) + res_values = result.values + res_indices = result.indices + + if not descending: + res_values = -result.values + + return TensorFlowTensor(res_values), TensorFlowTensor(res_indices) diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index e69de29bb2d..82ac65b9ff3 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -0,0 +1,55 @@ +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp + +from docarray.computation.tensorflow_backend import TensorFlowCompBackend +from docarray.typing import TensorFlowTensor + + +def test_top_k_descending_false(): + top_k = TensorFlowCompBackend.Retrieval.top_k + + a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) + vals, indices = top_k(a, 3, descending=False) + + assert vals.tensor.shape == (1, 3) + assert indices.tensor.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([1, 2, 2])) + assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([0, 2, 6])) or ( + tnp.allclose(tnp.squeeze.indices.tensor), + tf.constant([0, 6, 2]), + ) + + a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) + vals, indices = top_k(a, 3, descending=False) + assert vals.tensor.shape == (2, 3) + assert indices.tensor.shape == (2, 3) + assert tnp.allclose(vals.tensor[0], tf.constant([1, 2, 2])) + assert tnp.allclose(indices.tensor[0], tf.constant([0, 2, 6])) or tnp.allclose( + indices.tensor[0], tf.constant([0, 6, 2]) + ) + assert tnp.allclose(vals.tensor[1], tf.constant([2, 3, 4])) + assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) + + +def test_top_k_descending_true(): + top_k = TensorFlowCompBackend.Retrieval.top_k + + a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) + vals, indices = top_k(a, 3, descending=True) + + assert vals.tensor.shape == (1, 3) + assert indices.tensor.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([9, 7, 4])) + assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([5, 3, 1])) + + a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) + vals, indices = top_k(a, 3, descending=True) + + assert vals.tensor.shape == (2, 3) + assert indices.tensor.shape == (2, 3) + + assert tnp.allclose(vals.tensor[0], tf.constant([9, 7, 4])) + assert tnp.allclose(indices.tensor[0], tf.constant([0, 2, 6])) + + assert tnp.allclose(vals.tensor[1], tf.constant([11, 10, 7])) + assert tnp.allclose(indices.tensor[1], tf.constant([0, 5, 3])) From b0fd980d7496b286d807dbd526ca37599693d298 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 13:19:37 +0100 Subject: [PATCH 06/70] fix: extract methods that overlap for np and tf backend Signed-off-by: anna-charlotte --- docarray/computation/abstract_comp_backend.py | 15 ++-- .../abstract_numpy_based_backend.py | 63 +++++++++++++++ docarray/computation/numpy_backend.py | 54 +------------ docarray/computation/tensorflow_backend.py | 77 +++++-------------- docarray/computation/torch_backend.py | 23 +++--- docarray/typing/tensor/tensorflow_tensor.py | 2 +- .../numpy_backend/test_basics.py | 15 ++++ .../tensorflow_backend/test_basics.py | 40 ++++------ .../tensorflow_backend/test_retrieval.py | 53 +++++++------ 9 files changed, 166 insertions(+), 176 deletions(-) create mode 100644 docarray/computation/abstract_numpy_based_backend.py diff --git a/docarray/computation/abstract_comp_backend.py b/docarray/computation/abstract_comp_backend.py index d29af1c2cd4..01c5767884d 100644 --- a/docarray/computation/abstract_comp_backend.py +++ b/docarray/computation/abstract_comp_backend.py @@ -19,10 +19,10 @@ class AbstractComputationalBackend(ABC, typing.Generic[TTensor]): That way, DocArray can leverage native implementations from all frameworks. """ - @staticmethod + @classmethod @abstractmethod def stack( - tensors: Union[List['TTensor'], Tuple['TTensor']], dim: int = 0 + cls, tensors: Union[List['TTensor'], Tuple['TTensor']], dim: int = 0 ) -> 'TTensor': """ Stack a list of tensors along a new axis. @@ -53,9 +53,10 @@ def to_numpy(array: 'TTensor') -> 'np.ndarray': """ ... - @staticmethod + @classmethod @abstractmethod def empty( + cls, shape: Tuple[int, ...], dtype: Optional[Any] = None, device: Optional[Any] = None, @@ -80,9 +81,9 @@ def device(tensor: 'TTensor') -> Optional[str]: """Return device on which the tensor is allocated.""" ... - @staticmethod + @classmethod @abstractmethod - def shape(tensor: 'TTensor') -> Tuple[int, ...]: + def shape(cls, tensor: 'TTensor') -> Tuple[int, ...]: """Get shape of tensor""" ... @@ -116,9 +117,9 @@ def dtype(tensor: 'TTensor') -> Any: """Get the data type of the tensor.""" ... - @staticmethod + @classmethod @abstractmethod - def isnan(tensor: 'TTensor') -> 'TTensor': + def isnan(cls, tensor: 'TTensor') -> 'TTensor': """Check element-wise for nan and return result as a boolean array""" ... diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py new file mode 100644 index 00000000000..ab100ca0740 --- /dev/null +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -0,0 +1,63 @@ +import types +from typing import Any, List, Optional, Tuple, Union + +import numpy as np +import tensorflow as tf # type: ignore + +from docarray.computation import AbstractComputationalBackend + + +class AbstractNumpyBasedBackend( + AbstractComputationalBackend[Union[np.ndarray, tf.Tensor]] +): + _module: types.ModuleType + + @classmethod + def stack( + cls, tensors: Union[List['np.ndarray'], Tuple['np.ndarray']], dim: int = 0 + ) -> 'np.ndarray': + return cls._module.stack(tensors, axis=dim) + + @classmethod + def n_dim(cls, array: 'np.ndarray') -> int: + return cls._module.ndim(array) + + @classmethod + def squeeze(cls, tensor: 'np.ndarray') -> 'np.ndarray': + """ + Returns a tensor with all the dimensions of tensor of size 1 removed. + """ + return cls._module.squeeze(tensor) + + @classmethod + def empty( + cls, + shape: Tuple[int, ...], + dtype: Optional[Any] = None, + device: Optional[Any] = None, + ) -> 'np.ndarray': + if cls._module is np and device is not None: + raise NotImplementedError('Numpy does not support devices (GPU).') + return cls._module.empty(shape, dtype=dtype) + + @classmethod + def shape(cls, array: 'np.ndarray') -> Tuple[int, ...]: + """Get shape of array""" + return tuple(cls._module.shape(array)) + + @classmethod + def reshape(cls, array: 'np.ndarray', shape: Tuple[int, ...]) -> 'np.ndarray': + """ + Gives a new shape to array without changing its data. + + :param array: array to be reshaped + :param shape: the new shape + :return: a array with the same data and number of elements as array + but with the specified shape. + """ + return cls._module.reshape(array, shape) + + @classmethod + def isnan(cls, tensor: 'np.ndarray') -> 'np.ndarray': + """Check element-wise for nan and return result as a boolean array""" + return cls._module.isnan(tensor) diff --git a/docarray/computation/numpy_backend.py b/docarray/computation/numpy_backend.py index afa2733c074..950d3650549 100644 --- a/docarray/computation/numpy_backend.py +++ b/docarray/computation/numpy_backend.py @@ -1,9 +1,10 @@ import warnings -from typing import Any, List, Optional, Tuple, Union +from typing import Any, List, Optional, Tuple import numpy as np from docarray.computation import AbstractComputationalBackend +from docarray.computation.abstract_numpy_based_backend import AbstractNumpyBasedBackend def _expand_if_single_axis(*matrices: np.ndarray) -> List[np.ndarray]: @@ -29,16 +30,12 @@ def _expand_if_scalar(arr: np.ndarray) -> np.ndarray: return arr -class NumpyCompBackend(AbstractComputationalBackend[np.ndarray]): +class NumpyCompBackend(AbstractNumpyBasedBackend): """ Computational backend for Numpy. """ - @staticmethod - def stack( - tensors: Union[List['np.ndarray'], Tuple['np.ndarray']], dim: int = 0 - ) -> 'np.ndarray': - return np.stack(tensors, axis=dim) + _module = np @staticmethod def to_device(tensor: 'np.ndarray', device: str) -> 'np.ndarray': @@ -50,53 +47,15 @@ def device(tensor: 'np.ndarray') -> Optional[str]: """Return device on which the tensor is allocated.""" return None - @staticmethod - def n_dim(array: 'np.ndarray') -> int: - return array.ndim - - @staticmethod - def squeeze(tensor: 'np.ndarray') -> 'np.ndarray': - """ - Returns a tensor with all the dimensions of tensor of size 1 removed. - """ - return tensor.squeeze() - @staticmethod def to_numpy(array: 'np.ndarray') -> 'np.ndarray': return array - @staticmethod - def empty( - shape: Tuple[int, ...], - dtype: Optional[Any] = None, - device: Optional[Any] = None, - ) -> 'np.ndarray': - if device is not None: - raise NotImplementedError('Numpy does not support devices (GPU).') - return np.empty(shape, dtype=dtype) - @staticmethod def none_value() -> Any: """Provide a compatible value that represents None in numpy.""" return None - @staticmethod - def shape(array: 'np.ndarray') -> Tuple[int, ...]: - """Get shape of array""" - return array.shape - - @staticmethod - def reshape(array: 'np.ndarray', shape: Tuple[int, ...]) -> 'np.ndarray': - """ - Gives a new shape to array without changing its data. - - :param array: array to be reshaped - :param shape: the new shape - :return: a array with the same data and number of elements as array - but with the specified shape. - """ - return array.reshape(shape) - @staticmethod def detach(tensor: 'np.ndarray') -> 'np.ndarray': """ @@ -112,11 +71,6 @@ def dtype(tensor: 'np.ndarray') -> np.dtype: """Get the data type of the tensor.""" return tensor.dtype - @staticmethod - def isnan(tensor: 'np.ndarray') -> 'np.ndarray': - """Check element-wise for nan and return result as a boolean array""" - return np.isnan(tensor) - @staticmethod def minmax_normalize( tensor: 'np.ndarray', diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 745f0fd83a2..b322e8f37d6 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -1,90 +1,55 @@ import typing -from typing import Any, List, Optional, Tuple, Union +from typing import Optional, Tuple import numpy as np -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp +import tensorflow as tf # type: ignore +import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray.computation import AbstractComputationalBackend -from docarray.typing import TensorFlowTensor +from docarray.computation.abstract_numpy_based_backend import AbstractNumpyBasedBackend -class TensorFlowCompBackend(AbstractComputationalBackend[tf.Tensor]): +class TensorFlowCompBackend(AbstractNumpyBasedBackend): """ Computational backend for TensorFlow. """ - @staticmethod - def stack( - tensors: Union[List['TensorFlowTensor'], Tuple['TensorFlowTensor']], - dim: int = 0, - ) -> 'TensorFlowTensor': - return TensorFlowTensor(tnp.stack([t.tensor for t in tensors], axis=dim)) - - @staticmethod - def n_dim(array: 'TensorFlowTensor') -> int: - return tnp.ndim(array.tensor) - - @staticmethod - def squeeze(tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': - return TensorFlowTensor(tnp.squeeze(tensor.tensor)) - - @staticmethod - def to_numpy(array: 'TensorFlowTensor') -> 'np.ndarray': - return array.tensor.numpy() + _module = tnp @staticmethod - def empty( - shape: Tuple[int, ...], - dtype: Optional[Any] = None, - device: Optional[Any] = None, - ) -> 'TensorFlowTensor': - return TensorFlowTensor(tnp.empty(shape=shape, dtype=dtype)) + def to_numpy(array: 'tf.Tensor') -> 'np.ndarray': + return array.numpy() @staticmethod def none_value() -> typing.Any: return tf.constant(float('nan')) @staticmethod - def to_device(tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor': + def to_device(tensor: 'tf.Tensor', device: str) -> 'tf.Tensor': pass @staticmethod - def device(tensor: 'TensorFlowTensor') -> Optional[str]: + def device(tensor: 'tf.Tensor') -> Optional[str]: return tensor.device @staticmethod - def shape(tensor: 'TensorFlowTensor') -> Tuple[int, ...]: - return tuple(tnp.shape(tensor.tensor)) + def detach(tensor: 'tf.Tensor') -> 'tf.Tensor': + return tf.stop_gradient(tensor) @staticmethod - def reshape( - tensor: 'TensorFlowTensor', shape: Tuple[int, ...] - ) -> 'TensorFlowTensor': - return tf.reshape(tensor.tensor, shape) - - @staticmethod - def detach(tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': - return TensorFlowTensor(tf.stop_gradient(tensor)) - - @staticmethod - def dtype(tensor: 'TensorFlowTensor') -> tf.dtypes: - return tensor.tensor.dtype - - @staticmethod - def isnan(tensor: 'TensorFlowTensor') -> TensorFlowTensor: - return TensorFlowTensor(tnp.isnan(tensor.tensor)) + def dtype(tensor: 'tf.Tensor') -> tf.dtypes: + return tensor.dtype @staticmethod def minmax_normalize( - tensor: 'TensorFlowTensor', + tensor: 'tf.Tensor', t_range: Tuple = (0.0, 1.0), x_range: Optional[Tuple] = None, eps: float = 1e-7, - ) -> 'TensorFlowTensor': + ) -> 'tf.Tensor': a, b = t_range - t = tf.cast(tensor.tensor, tf.float32) + t = tf.cast(tensor, tf.float32) min_d = x_range[0] if x_range else tnp.min(t, axis=-1, keepdims=True) max_d = x_range[1] if x_range else tnp.max(t, axis=-1, keepdims=True) @@ -92,7 +57,7 @@ def minmax_normalize( print(f"i = {i}") normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) - return tf.cast(normalized, tensor.tensor.dtype) + return tf.cast(normalized, tensor.dtype) class Retrieval(AbstractComputationalBackend.Retrieval[tf.Tensor]): """ @@ -101,7 +66,7 @@ class Retrieval(AbstractComputationalBackend.Retrieval[tf.Tensor]): @staticmethod def top_k( - values: 'TensorFlowTensor', + values: 'tf.Tensor', k: int, descending: bool = False, device: Optional[str] = None, @@ -123,9 +88,9 @@ def top_k( :return: Tuple containing the retrieved values, and their indices. Both ar of shape (n_queries, k) """ - values = values.tensor if device is not None: values = values.to(device) + if len(values.shape) <= 1: values = tf.expand_dims(values, axis=0) @@ -142,4 +107,4 @@ def top_k( if not descending: res_values = -result.values - return TensorFlowTensor(res_values), TensorFlowTensor(res_indices) + return res_values, res_indices diff --git a/docarray/computation/torch_backend.py b/docarray/computation/torch_backend.py index c05f9fb4c29..3774b07a66d 100644 --- a/docarray/computation/torch_backend.py +++ b/docarray/computation/torch_backend.py @@ -34,9 +34,9 @@ class TorchCompBackend(AbstractComputationalBackend[torch.Tensor]): Computational backend for PyTorch. """ - @staticmethod + @classmethod def stack( - tensors: Union[List['torch.Tensor'], Tuple['torch.Tensor']], dim: int = 0 + cls, tensors: Union[List['torch.Tensor'], Tuple['torch.Tensor']], dim: int = 0 ) -> 'torch.Tensor': return torch.stack(tensors, dim=dim) @@ -50,8 +50,9 @@ def device(tensor: 'torch.Tensor') -> Optional[str]: """Return device on which the tensor is allocated.""" return str(tensor.device) - @staticmethod + @classmethod def empty( + cls, shape: Tuple[int, ...], dtype: Optional[Any] = None, device: Optional[Any] = None, @@ -64,8 +65,8 @@ def empty( return torch.empty(shape, **extra_param) - @staticmethod - def n_dim(array: 'torch.Tensor') -> int: + @classmethod + def n_dim(cls, array: 'torch.Tensor') -> int: return array.ndim @staticmethod @@ -84,12 +85,12 @@ def none_value() -> Any: """Provide a compatible value that represents None in torch.""" return torch.tensor(float('nan')) - @staticmethod - def shape(tensor: 'torch.Tensor') -> Tuple[int, ...]: + @classmethod + def shape(cls, tensor: 'torch.Tensor') -> Tuple[int, ...]: return tuple(tensor.shape) - @staticmethod - def reshape(tensor: 'torch.Tensor', shape: Tuple[int, ...]) -> 'torch.Tensor': + @classmethod + def reshape(cls, tensor: 'torch.Tensor', shape: Tuple[int, ...]) -> 'torch.Tensor': """ Gives a new shape to tensor without changing its data. @@ -116,8 +117,8 @@ def dtype(tensor: 'torch.Tensor') -> torch.dtype: """Get the data type of the tensor.""" return tensor.dtype - @staticmethod - def isnan(tensor: 'torch.Tensor') -> 'torch.Tensor': + @classmethod + def isnan(cls, tensor: 'torch.Tensor') -> 'torch.Tensor': """Check element-wise for nan and return result as a boolean array""" return torch.isnan(tensor) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index a653eb3751f..dee156217aa 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -1,7 +1,7 @@ from typing import TYPE_CHECKING, Any, Dict, Generic, Type, TypeVar, Union import numpy as np -import tensorflow as tf +import tensorflow as tf # type: ignore from docarray.typing.proto_register import _register_proto from docarray.typing.tensor.abstract_tensor import AbstractTensor diff --git a/tests/units/computation_backends/numpy_backend/test_basics.py b/tests/units/computation_backends/numpy_backend/test_basics.py index 29cebb0d22b..fde525a459f 100644 --- a/tests/units/computation_backends/numpy_backend/test_basics.py +++ b/tests/units/computation_backends/numpy_backend/test_basics.py @@ -1,7 +1,9 @@ import numpy as np import pytest +from pydantic import parse_obj_as from docarray.computation.numpy_backend import NumpyCompBackend +from docarray.typing import NdArray def test_to_device(): @@ -87,3 +89,16 @@ def test_minmax_normalize(array, t_range, x_range, result): tensor=array, t_range=t_range, x_range=x_range ) assert np.allclose(output, result) + + +def test_stack(): + t0 = parse_obj_as(NdArray, np.zeros((3, 224, 224))) + t1 = parse_obj_as(NdArray, np.ones((3, 224, 224))) + + stacked1 = NumpyCompBackend.stack([t0, t1], dim=0) + assert isinstance(stacked1, np.ndarray) + assert stacked1.shape == (2, 3, 224, 224) + + stacked2 = NumpyCompBackend.stack([t0, t1], dim=-1) + assert isinstance(stacked2, np.ndarray) + assert stacked2.shape == (3, 224, 224, 2) diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 8077e175084..835f01d3c3a 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -3,12 +3,6 @@ import tensorflow as tf from docarray.computation.tensorflow_backend import TensorFlowCompBackend -from docarray.typing import TensorFlowTensor - - -def test_to_device(): - with pytest.raises(NotImplementedError): - TensorFlowCompBackend.to_device(tf.zeros((10, 3)), 'CPU:0') @pytest.mark.parametrize( @@ -21,7 +15,6 @@ def test_to_device(): ], ) def test_n_dim(array, result): - array = TensorFlowTensor(array) assert TensorFlowCompBackend.n_dim(array) == result @@ -34,32 +27,31 @@ def test_n_dim(array, result): ], ) def test_shape(array, result): - array = TensorFlowTensor(array) shape = TensorFlowCompBackend.shape(array) assert shape == result assert type(shape) == tuple # def test_device(): -# array = tf.constant([1, 2, 3]) +# array = tf.constant([1, 2, 3])x # assert TensorFlowCompBackend.device(array) is not None @pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) def test_dtype(dtype): - array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=dtype)) + array = tf.constant([1, 2, 3], dtype=dtype) assert TensorFlowCompBackend.dtype(array) == dtype def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) - assert array.tensor.shape == (10, 3) + assert array.shape == (10, 3) def test_empty_dtype(): tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) - assert tf_tensor.tensor.shape == (10, 3) - assert tf_tensor.tensor.dtype == tf.int32 + assert tf_tensor.shape == (10, 3) + assert tf_tensor.dtype == tf.int32 # def test_empty_device(): @@ -68,9 +60,9 @@ def test_empty_dtype(): def test_squeeze(): - tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) + tensor = tf.zeros(shape=(1, 1, 3, 1)) squeezed = TensorFlowCompBackend.squeeze(tensor) - assert squeezed.tensor.shape == (3,) + assert squeezed.shape == (3,) @pytest.mark.parametrize( @@ -98,25 +90,25 @@ def test_squeeze(): ) def test_minmax_normalize(array, t_range, x_range, result): output = TensorFlowCompBackend.minmax_normalize( - tensor=TensorFlowTensor(array), t_range=t_range, x_range=x_range + tensor=array, t_range=t_range, x_range=x_range ) assert np.allclose(output, result) def test_reshape(): - tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) + tensor = tf.zeros((3, 224, 224)) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) - assert reshaped.tensor.shape == (224, 224, 3) + assert reshaped.shape == (224, 224, 3) def test_stack(): - t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) - t1 = TensorFlowTensor(tf.ones((3, 224, 224))) + t0 = tf.zeros((3, 224, 224)) + t1 = tf.ones((3, 224, 224)) stacked1 = TensorFlowCompBackend.stack([t0, t1], dim=0) - assert isinstance(stacked1, TensorFlowTensor) - assert stacked1.tensor.shape == (2, 3, 224, 224) + assert isinstance(stacked1, tf.Tensor) + assert stacked1.shape == (2, 3, 224, 224) stacked2 = TensorFlowCompBackend.stack([t0, t1], dim=-1) - assert isinstance(stacked2, TensorFlowTensor) - assert stacked2.tensor.shape == (3, 224, 224, 2) + assert isinstance(stacked2, tf.Tensor) + assert stacked2.shape == (3, 224, 224, 2) diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 82ac65b9ff3..e20831a4c04 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -2,54 +2,53 @@ import tensorflow._api.v2.experimental.numpy as tnp from docarray.computation.tensorflow_backend import TensorFlowCompBackend -from docarray.typing import TensorFlowTensor def test_top_k_descending_false(): top_k = TensorFlowCompBackend.Retrieval.top_k - a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) + a = tf.constant([1, 4, 2, 7, 4, 9, 2]) vals, indices = top_k(a, 3, descending=False) - assert vals.tensor.shape == (1, 3) - assert indices.tensor.shape == (1, 3) - assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([1, 2, 2])) - assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([0, 2, 6])) or ( - tnp.allclose(tnp.squeeze.indices.tensor), + assert vals.shape == (1, 3) + assert indices.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals), tf.constant([1, 2, 2])) + assert tnp.allclose(tnp.squeeze(indices), tf.constant([0, 2, 6])) or ( + tnp.allclose(tnp.squeeze.indices), tf.constant([0, 6, 2]), ) - a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) + a = tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]]) vals, indices = top_k(a, 3, descending=False) - assert vals.tensor.shape == (2, 3) - assert indices.tensor.shape == (2, 3) - assert tnp.allclose(vals.tensor[0], tf.constant([1, 2, 2])) - assert tnp.allclose(indices.tensor[0], tf.constant([0, 2, 6])) or tnp.allclose( - indices.tensor[0], tf.constant([0, 6, 2]) + assert vals.shape == (2, 3) + assert indices.shape == (2, 3) + assert tnp.allclose(vals[0], tf.constant([1, 2, 2])) + assert tnp.allclose(indices[0], tf.constant([0, 2, 6])) or tnp.allclose( + indices[0], tf.constant([0, 6, 2]) ) - assert tnp.allclose(vals.tensor[1], tf.constant([2, 3, 4])) - assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) + assert tnp.allclose(vals[1], tf.constant([2, 3, 4])) + assert tnp.allclose(indices[1], tf.constant([2, 4, 6])) def test_top_k_descending_true(): top_k = TensorFlowCompBackend.Retrieval.top_k - a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) + a = tf.constant([1, 4, 2, 7, 4, 9, 2]) vals, indices = top_k(a, 3, descending=True) - assert vals.tensor.shape == (1, 3) - assert indices.tensor.shape == (1, 3) - assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([9, 7, 4])) - assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([5, 3, 1])) + assert vals.shape == (1, 3) + assert indices.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals), tf.constant([9, 7, 4])) + assert tnp.allclose(tnp.squeeze(indices), tf.constant([5, 3, 1])) - a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) + a = tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]]) vals, indices = top_k(a, 3, descending=True) - assert vals.tensor.shape == (2, 3) - assert indices.tensor.shape == (2, 3) + assert vals.shape == (2, 3) + assert indices.shape == (2, 3) - assert tnp.allclose(vals.tensor[0], tf.constant([9, 7, 4])) - assert tnp.allclose(indices.tensor[0], tf.constant([0, 2, 6])) + assert tnp.allclose(vals[0], tf.constant([9, 7, 4])) + assert tnp.allclose(indices[0], tf.constant([0, 2, 6])) - assert tnp.allclose(vals.tensor[1], tf.constant([11, 10, 7])) - assert tnp.allclose(indices.tensor[1], tf.constant([0, 5, 3])) + assert tnp.allclose(vals[1], tf.constant([11, 10, 7])) + assert tnp.allclose(indices[1], tf.constant([0, 5, 3])) From c2e6ab0a3fe9132796ff0cdf899ad43a9d055768 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 13:27:26 +0100 Subject: [PATCH 07/70] fix: revert poetry lock change Signed-off-by: anna-charlotte --- poetry.lock | 2396 +++++++++++++++++++++++++-------------------------- 1 file changed, 1198 insertions(+), 1198 deletions(-) diff --git a/poetry.lock b/poetry.lock index 97fc74465e7..719cf8dd921 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,3 +1,5 @@ +# This file is automatically @generated by Poetry and should not be changed by hand. + [[package]] name = "anyio" version = "3.6.2" @@ -5,6 +7,10 @@ description = "High level compatibility layer for multiple asynchronous event lo category = "main" optional = false python-versions = ">=3.6.2" +files = [ + {file = "anyio-3.6.2-py3-none-any.whl", hash = "sha256:fbbe32bd270d2a2ef3ed1c5d45041250284e31fc0a4df4a5a6071842051a51e3"}, + {file = "anyio-3.6.2.tar.gz", hash = "sha256:25ea0d673ae30af41a0c442f81cf3b38c7e79fdc7b60335a4c14e05eb0947421"}, +] [package.dependencies] idna = ">=2.8" @@ -23,6 +29,10 @@ description = "Disable App Nap on macOS >= 10.9" category = "dev" optional = false python-versions = "*" +files = [ + {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"}, + {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"}, +] [[package]] name = "argon2-cffi" @@ -31,6 +41,10 @@ description = "The secure Argon2 password hashing algorithm." category = "dev" optional = false python-versions = ">=3.6" +files = [ + {file = "argon2-cffi-21.3.0.tar.gz", hash = "sha256:d384164d944190a7dd7ef22c6aa3ff197da12962bd04b17f64d4e93d934dba5b"}, + {file = "argon2_cffi-21.3.0-py3-none-any.whl", hash = "sha256:8c976986f2c5c0e5000919e6de187906cfd81fb1c72bf9d88c01177e77da7f80"}, +] [package.dependencies] argon2-cffi-bindings = "*" @@ -48,6 +62,29 @@ description = "Low-level CFFI bindings for Argon2" category = "dev" optional = false python-versions = ">=3.6" +files = [ + {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"}, + {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"}, + {file = 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From cf6a0ef338c75498b43a4065f5ebe5df248da1be Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 16:43:46 +0100 Subject: [PATCH 08/70] fix: introduce norm callables to transform tftensor Signed-off-by: anna-charlotte --- docarray/computation/abstract_comp_backend.py | 39 ++-- .../abstract_numpy_based_backend.py | 42 ++--- docarray/computation/numpy_backend.py | 38 ++-- docarray/computation/tensorflow_backend.py | 171 +++++++++++++++--- docarray/computation/torch_backend.py | 41 +++-- .../tensorflow_backend/test_basics.py | 48 ++--- 6 files changed, 260 insertions(+), 119 deletions(-) diff --git a/docarray/computation/abstract_comp_backend.py b/docarray/computation/abstract_comp_backend.py index 01c5767884d..b351bedcfcb 100644 --- a/docarray/computation/abstract_comp_backend.py +++ b/docarray/computation/abstract_comp_backend.py @@ -29,25 +29,25 @@ def stack( """ ... - @staticmethod + @classmethod @abstractmethod - def n_dim(array: 'TTensor') -> int: + def n_dim(cls, array: 'TTensor') -> int: """ Get the number of the array dimensions. """ ... - @staticmethod + @classmethod @abstractmethod - def squeeze(tensor: 'TTensor') -> 'TTensor': + def squeeze(cls, tensor: 'TTensor') -> 'TTensor': """ Returns a tensor with all the dimensions of tensor of size 1 removed. """ ... - @staticmethod + @classmethod @abstractmethod - def to_numpy(array: 'TTensor') -> 'np.ndarray': + def to_numpy(cls, array: 'TTensor') -> 'np.ndarray': """ Convert array to np.ndarray. """ @@ -63,21 +63,21 @@ def empty( ) -> 'TTensor': ... - @staticmethod + @classmethod @abstractmethod - def none_value() -> typing.Any: + def none_value(cls) -> typing.Any: """Provide a compatible value that represents None in the Tensor Backend.""" ... - @staticmethod + @classmethod @abstractmethod - def to_device(tensor: 'TTensor', device: str) -> 'TTensor': + def to_device(cls, tensor: 'TTensor', device: str) -> 'TTensor': """Move the tensor to the specified device.""" ... - @staticmethod + @classmethod @abstractmethod - def device(tensor: 'TTensor') -> Optional[str]: + def device(cls, tensor: 'TTensor') -> Optional[str]: """Return device on which the tensor is allocated.""" ... @@ -87,9 +87,9 @@ def shape(cls, tensor: 'TTensor') -> Tuple[int, ...]: """Get shape of tensor""" ... - @staticmethod + @classmethod @abstractmethod - def reshape(tensor: 'TTensor', shape: Tuple[int, ...]) -> 'TTensor': + def reshape(cls, tensor: 'TTensor', shape: Tuple[int, ...]) -> 'TTensor': """ Gives a new shape to tensor without changing its data. @@ -100,9 +100,9 @@ def reshape(tensor: 'TTensor', shape: Tuple[int, ...]) -> 'TTensor': """ ... - @staticmethod + @classmethod @abstractmethod - def detach(tensor: 'TTensor') -> 'TTensor': + def detach(cls, tensor: 'TTensor') -> 'TTensor': """ Returns the tensor detached from its current graph. @@ -111,9 +111,9 @@ def detach(tensor: 'TTensor') -> 'TTensor': """ ... - @staticmethod + @classmethod @abstractmethod - def dtype(tensor: 'TTensor') -> Any: + def dtype(cls, tensor: 'TTensor') -> Any: """Get the data type of the tensor.""" ... @@ -123,9 +123,10 @@ def isnan(cls, tensor: 'TTensor') -> 'TTensor': """Check element-wise for nan and return result as a boolean array""" ... - @staticmethod + @classmethod @abstractmethod def minmax_normalize( + cls, tensor: 'TTensor', t_range: Tuple = (0, 1), x_range: Optional[Tuple] = None, diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py index ab100ca0740..94a5a4a4ec1 100644 --- a/docarray/computation/abstract_numpy_based_backend.py +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -1,33 +1,33 @@ import types -from typing import Any, List, Optional, Tuple, Union +from typing import Any, Callable, List, Optional, Tuple, TypeVar, Union import numpy as np -import tensorflow as tf # type: ignore from docarray.computation import AbstractComputationalBackend +T = TypeVar('T') -class AbstractNumpyBasedBackend( - AbstractComputationalBackend[Union[np.ndarray, tf.Tensor]] -): + +class AbstractNumpyBasedBackend(AbstractComputationalBackend[T]): _module: types.ModuleType + _norm_left: Callable + _norm_right: Callable @classmethod - def stack( - cls, tensors: Union[List['np.ndarray'], Tuple['np.ndarray']], dim: int = 0 - ) -> 'np.ndarray': - return cls._module.stack(tensors, axis=dim) + def stack(cls, tensors: Union[List[T], Tuple[T]], dim: int = 0) -> T: + norm_right = [cls._norm_right(t) for t in tensors] + return cls._norm_left(cls._module.stack(norm_right, axis=dim)) @classmethod - def n_dim(cls, array: 'np.ndarray') -> int: - return cls._module.ndim(array) + def n_dim(cls, array: T) -> int: + return cls._module.ndim(cls._norm_right(array)) @classmethod - def squeeze(cls, tensor: 'np.ndarray') -> 'np.ndarray': + def squeeze(cls, tensor: T) -> T: """ Returns a tensor with all the dimensions of tensor of size 1 removed. """ - return cls._module.squeeze(tensor) + return cls._norm_left(cls._module.squeeze(cls._norm_right(tensor))) @classmethod def empty( @@ -35,18 +35,18 @@ def empty( shape: Tuple[int, ...], dtype: Optional[Any] = None, device: Optional[Any] = None, - ) -> 'np.ndarray': + ) -> T: if cls._module is np and device is not None: raise NotImplementedError('Numpy does not support devices (GPU).') - return cls._module.empty(shape, dtype=dtype) + return cls._norm_left(cls._module.empty(shape, dtype=dtype)) @classmethod - def shape(cls, array: 'np.ndarray') -> Tuple[int, ...]: + def shape(cls, array: T) -> Tuple[int, ...]: """Get shape of array""" - return tuple(cls._module.shape(array)) + return tuple(cls._module.shape(cls._norm_right(array))) @classmethod - def reshape(cls, array: 'np.ndarray', shape: Tuple[int, ...]) -> 'np.ndarray': + def reshape(cls, array: T, shape: Tuple[int, ...]) -> T: """ Gives a new shape to array without changing its data. @@ -55,9 +55,9 @@ def reshape(cls, array: 'np.ndarray', shape: Tuple[int, ...]) -> 'np.ndarray': :return: a array with the same data and number of elements as array but with the specified shape. """ - return cls._module.reshape(array, shape) + return cls._norm_left(cls._module.reshape(cls._norm_right(array), shape)) @classmethod - def isnan(cls, tensor: 'np.ndarray') -> 'np.ndarray': + def isnan(cls, tensor: T) -> T: """Check element-wise for nan and return result as a boolean array""" - return cls._module.isnan(tensor) + return cls._norm_left(cls._module.isnan(cls._norm_right(tensor))) diff --git a/docarray/computation/numpy_backend.py b/docarray/computation/numpy_backend.py index 950d3650549..000a6636103 100644 --- a/docarray/computation/numpy_backend.py +++ b/docarray/computation/numpy_backend.py @@ -30,34 +30,42 @@ def _expand_if_scalar(arr: np.ndarray) -> np.ndarray: return arr +def identity(array: np.ndarray) -> np.ndarray: + return array + + class NumpyCompBackend(AbstractNumpyBasedBackend): """ Computational backend for Numpy. """ _module = np + _norm_left = identity + _norm_right = identity - @staticmethod - def to_device(tensor: 'np.ndarray', device: str) -> 'np.ndarray': + @classmethod + def to_device(cls, tensor: 'np.ndarray', device: str) -> 'np.ndarray': """Move the tensor to the specified device.""" raise NotImplementedError('Numpy does not support devices (GPU).') - @staticmethod - def device(tensor: 'np.ndarray') -> Optional[str]: + @classmethod + def device(cls, tensor: 'np.ndarray') -> Optional[str]: """Return device on which the tensor is allocated.""" return None - @staticmethod - def to_numpy(array: 'np.ndarray') -> 'np.ndarray': + @classmethod + def to_numpy(cls, array: 'np.ndarray') -> 'np.ndarray': return array - @staticmethod - def none_value() -> Any: + @classmethod + def none_value( + cls, + ) -> Any: """Provide a compatible value that represents None in numpy.""" return None - @staticmethod - def detach(tensor: 'np.ndarray') -> 'np.ndarray': + @classmethod + def detach(cls, tensor: 'np.ndarray') -> 'np.ndarray': """ Returns the tensor detached from its current graph. @@ -66,13 +74,14 @@ def detach(tensor: 'np.ndarray') -> 'np.ndarray': """ return tensor - @staticmethod - def dtype(tensor: 'np.ndarray') -> np.dtype: + @classmethod + def dtype(cls, tensor: 'np.ndarray') -> np.dtype: """Get the data type of the tensor.""" return tensor.dtype - @staticmethod + @classmethod def minmax_normalize( + cls, tensor: 'np.ndarray', t_range: Tuple = (0, 1), x_range: Optional[Tuple] = None, @@ -108,8 +117,9 @@ class Retrieval(AbstractComputationalBackend.Retrieval[np.ndarray]): Abstract class for retrieval and ranking functionalities """ - @staticmethod + @classmethod def top_k( + cls, values: 'np.ndarray', k: int, descending: bool = False, diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index b322e8f37d6..c9ba6c7e64f 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -1,5 +1,5 @@ import typing -from typing import Optional, Tuple +from typing import Callable, List, Optional, Tuple import numpy as np import tensorflow as tf # type: ignore @@ -7,57 +7,97 @@ from docarray.computation import AbstractComputationalBackend from docarray.computation.abstract_numpy_based_backend import AbstractNumpyBasedBackend +from docarray.typing import TensorFlowTensor -class TensorFlowCompBackend(AbstractNumpyBasedBackend): +def _unsqueeze_if_single_axis(*matrices: tf.Tensor) -> List[tf.Tensor]: + """Unsqueezes tensors that only have one axis, at dim 0. + This ensures that all outputs can be treated as matrices, not vectors. + + :param matrices: Matrices to be unsqueezed + :return: List of the input matrices, + where single axis matrices are unsqueezed at dim 0. + """ + unsqueezed = [] + for m in matrices: + if len(m.shape) == 1: + unsqueezed.append(tf.expand_dims(m, axis=0)) + else: + unsqueezed.append(m) + return unsqueezed + + +def _unsqueeze_if_scalar(t: tf.Tensor): + if len(t.shape) == 0: # avoid scalar output + t = t.unsqueeze(0) + return t + + +def norm_left(t: tf.Tensor) -> TensorFlowTensor: + return TensorFlowTensor(tensor=t) + + +def norm_right(t: TensorFlowTensor) -> tf.Tensor: + return t.tensor + + +class TensorFlowCompBackend(AbstractNumpyBasedBackend[TensorFlowTensor]): """ Computational backend for TensorFlow. """ _module = tnp + _norm_left: Callable = norm_left + _norm_right: Callable = norm_right - @staticmethod - def to_numpy(array: 'tf.Tensor') -> 'np.ndarray': - return array.numpy() + @classmethod + def to_numpy(cls, array: 'TensorFlowTensor') -> 'np.ndarray': + return cls._norm_right(array).numpy() - @staticmethod - def none_value() -> typing.Any: + @classmethod + def none_value( + cls, + ) -> typing.Any: return tf.constant(float('nan')) - @staticmethod - def to_device(tensor: 'tf.Tensor', device: str) -> 'tf.Tensor': - pass + @classmethod + def to_device(cls, tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor': + if cls.device(tensor) == device: + return tensor + else: + with tf.device(device): + return cls._norm_left(tf.identity(cls._norm_right(tensor))) - @staticmethod - def device(tensor: 'tf.Tensor') -> Optional[str]: - return tensor.device + @classmethod + def device(cls, tensor: 'TensorFlowTensor') -> Optional[str]: + return cls._norm_right(tensor).device - @staticmethod - def detach(tensor: 'tf.Tensor') -> 'tf.Tensor': - return tf.stop_gradient(tensor) + @classmethod + def detach(cls, tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': + return cls._norm_left(tf.stop_gradient(cls._norm_right(tensor))) - @staticmethod - def dtype(tensor: 'tf.Tensor') -> tf.dtypes: - return tensor.dtype + @classmethod + def dtype(cls, tensor: 'TensorFlowTensor') -> tf.dtypes: + return cls._norm_right(tensor).dtype - @staticmethod + @classmethod def minmax_normalize( - tensor: 'tf.Tensor', + cls, + tensor: 'TensorFlowTensor', t_range: Tuple = (0.0, 1.0), x_range: Optional[Tuple] = None, eps: float = 1e-7, - ) -> 'tf.Tensor': + ) -> 'TensorFlowTensor': a, b = t_range - t = tf.cast(tensor, tf.float32) + t = tf.cast(cls._norm_right(tensor), tf.float32) min_d = x_range[0] if x_range else tnp.min(t, axis=-1, keepdims=True) max_d = x_range[1] if x_range else tnp.max(t, axis=-1, keepdims=True) i = (b - a) * (t - min_d) / (max_d - min_d + tf.constant(eps) + a) - print(f"i = {i}") normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) - return tf.cast(normalized, tensor.dtype) + return cls._norm_left(tf.cast(normalized, tensor.tensor.dtype)) class Retrieval(AbstractComputationalBackend.Retrieval[tf.Tensor]): """ @@ -108,3 +148,84 @@ def top_k( res_values = -result.values return res_values, res_indices + + class Metrics(AbstractComputationalBackend.Metrics[tf.Tensor]): + """ + Abstract base class for metrics (distances and similarities). + """ + + @staticmethod + def cosine_sim( + x_mat: 'tf.Tensor', + y_mat: 'tf.Tensor', + eps: float = 1e-7, + device: Optional[str] = None, + ) -> 'tf.Tensor': + """Pairwise cosine similarities between all vectors in x_mat and y_mat. + + :param x_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each example. + :param y_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each example. + :param eps: a small jitter to avoid divde by zero + :param device: the device to use for computations. + If not provided, the devices of x_mat and y_mat are used. + :return: Tensor of shape (n_vectors, n_vectors) containing all pairwise + cosine distances. + The index [i_x, i_y] contains the cosine distance between + x_mat[i_x] and y_mat[i_y]. + """ + if device is not None: + with tf.device(device): + x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) + + a_n, b_n = x_mat.norm(dim=1)[:, None], y_mat.norm(dim=1)[:, None] + a_norm = x_mat / tf.clamp(a_n, min=eps) + b_norm = y_mat / tf.clamp(b_n, min=eps) + sims = tf.mm(a_norm, b_norm.transpose(0, 1)).squeeze() + return _unsqueeze_if_scalar(sims) + + @staticmethod + def euclidean_dist( + x_mat: 'tf.Tensor', + y_mat: 'tf.Tensor', + device: Optional[str] = None, + ) -> 'tf.Tensor': + """Pairwise Euclidian distances between all vectors in x_mat and y_mat. + + :param x_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each example. + :param y_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each example. + :param device: the device to use for pytorch computations. + If not provided, the devices of x_mat and y_mat are used. + :return: Tensor of shape (n_vectors, n_vectors) containing all pairwise + euclidian distances. + The index [i_x, i_y] contains the euclidian distance between + x_mat[i_x] and y_mat[i_y]. + """ + ... + + @staticmethod + def sqeuclidean_dist( + x_mat: 'tf.Tensor', + y_mat: 'tf.Tensor', + device: Optional[str] = None, + ) -> 'tf.Tensor': + """Pairwise Squared Euclidian distances between all vectors + in x_mat and y_mat. + + :param x_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each + example. + :param y_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the + number of vectors and n_dim is the number of dimensions of each + example. + :param device: the device to use for pytorch computations. + If not provided, the devices of x_mat and y_mat are used. + :return: Tensor of shape (n_vectors, n_vectors) containing all pairwise + euclidian distances. + The index [i_x, i_y] contains the euclidian distance between + x_mat[i_x] and y_mat[i_y]. + """ + ... diff --git a/docarray/computation/torch_backend.py b/docarray/computation/torch_backend.py index 3774b07a66d..936b16f3188 100644 --- a/docarray/computation/torch_backend.py +++ b/docarray/computation/torch_backend.py @@ -23,7 +23,7 @@ def _unsqueeze_if_single_axis(*matrices: torch.Tensor) -> List[torch.Tensor]: return unsqueezed -def _usqueeze_if_scalar(t: torch.Tensor): +def _unsqueeze_if_scalar(t: torch.Tensor): if len(t.shape) == 0: # avoid scalar output t = t.unsqueeze(0) return t @@ -40,13 +40,13 @@ def stack( ) -> 'torch.Tensor': return torch.stack(tensors, dim=dim) - @staticmethod - def to_device(tensor: 'torch.Tensor', device: str) -> 'torch.Tensor': + @classmethod + def to_device(cls, tensor: 'torch.Tensor', device: str) -> 'torch.Tensor': """Move the tensor to the specified device.""" return tensor.to(device) - @staticmethod - def device(tensor: 'torch.Tensor') -> Optional[str]: + @classmethod + def device(cls, tensor: 'torch.Tensor') -> Optional[str]: """Return device on which the tensor is allocated.""" return str(tensor.device) @@ -69,19 +69,21 @@ def empty( def n_dim(cls, array: 'torch.Tensor') -> int: return array.ndim - @staticmethod - def squeeze(tensor: 'torch.Tensor') -> 'torch.Tensor': + @classmethod + def squeeze(cls, tensor: 'torch.Tensor') -> 'torch.Tensor': """ Returns a tensor with all the dimensions of tensor of size 1 removed. """ return torch.squeeze(tensor) - @staticmethod - def to_numpy(array: 'torch.Tensor') -> 'np.ndarray': + @classmethod + def to_numpy(cls, array: 'torch.Tensor') -> 'np.ndarray': return array.cpu().detach().numpy() - @staticmethod - def none_value() -> Any: + @classmethod + def none_value( + cls, + ) -> Any: """Provide a compatible value that represents None in torch.""" return torch.tensor(float('nan')) @@ -102,8 +104,8 @@ def reshape(cls, tensor: 'torch.Tensor', shape: Tuple[int, ...]) -> 'torch.Tenso """ return tensor.reshape(shape) - @staticmethod - def detach(tensor: 'torch.Tensor') -> 'torch.Tensor': + @classmethod + def detach(cls, tensor: 'torch.Tensor') -> 'torch.Tensor': """ Returns the tensor detached from its current graph. @@ -112,8 +114,8 @@ def detach(tensor: 'torch.Tensor') -> 'torch.Tensor': """ return tensor.detach() - @staticmethod - def dtype(tensor: 'torch.Tensor') -> torch.dtype: + @classmethod + def dtype(cls, tensor: 'torch.Tensor') -> torch.dtype: """Get the data type of the tensor.""" return tensor.dtype @@ -122,8 +124,9 @@ def isnan(cls, tensor: 'torch.Tensor') -> 'torch.Tensor': """Check element-wise for nan and return result as a boolean array""" return torch.isnan(tensor) - @staticmethod + @classmethod def minmax_normalize( + cls, tensor: 'torch.Tensor', t_range: Tuple = (0, 1), x_range: Optional[Tuple] = None, @@ -235,7 +238,7 @@ def cosine_sim( a_norm = x_mat / torch.clamp(a_n, min=eps) b_norm = y_mat / torch.clamp(b_n, min=eps) sims = torch.mm(a_norm, b_norm.transpose(0, 1)).squeeze() - return _usqueeze_if_scalar(sims) + return _unsqueeze_if_scalar(sims) @staticmethod def euclidean_dist( @@ -262,7 +265,7 @@ def euclidean_dist( x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) dists = torch.cdist(x_mat, y_mat).squeeze() - return _usqueeze_if_scalar(dists) + return _unsqueeze_if_scalar(dists) @staticmethod def sqeuclidean_dist( @@ -290,4 +293,4 @@ def sqeuclidean_dist( x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) - return _usqueeze_if_scalar((torch.cdist(x_mat, y_mat) ** 2).squeeze()) + return _unsqueeze_if_scalar((torch.cdist(x_mat, y_mat) ** 2).squeeze()) diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 835f01d3c3a..286042e6bc6 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -3,6 +3,7 @@ import tensorflow as tf from docarray.computation.tensorflow_backend import TensorFlowCompBackend +from docarray.typing import TensorFlowTensor @pytest.mark.parametrize( @@ -15,6 +16,7 @@ ], ) def test_n_dim(array, result): + array = TensorFlowTensor(array) assert TensorFlowCompBackend.n_dim(array) == result @@ -27,42 +29,45 @@ def test_n_dim(array, result): ], ) def test_shape(array, result): + array = TensorFlowTensor(array) shape = TensorFlowCompBackend.shape(array) assert shape == result assert type(shape) == tuple -# def test_device(): -# array = tf.constant([1, 2, 3])x -# assert TensorFlowCompBackend.device(array) is not None +def test_to_device(): + array = TensorFlowTensor(tf.constant([1, 2, 3])) + array = TensorFlowCompBackend.to_device(array, 'CPU:0') + assert array.tensor.device.endswith('CPU:0') @pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) def test_dtype(dtype): - array = tf.constant([1, 2, 3], dtype=dtype) + array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=dtype)) assert TensorFlowCompBackend.dtype(array) == dtype def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) - assert array.shape == (10, 3) + assert array.tensor.shape == (10, 3) def test_empty_dtype(): tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) - assert tf_tensor.shape == (10, 3) - assert tf_tensor.dtype == tf.int32 + assert tf_tensor.tensor.shape == (10, 3) + assert tf_tensor.tensor.dtype == tf.int32 -# def test_empty_device(): -# with pytest.raises(NotImplementedError): -# TensorFlowCompBackend.empty((10, 3), device='CPU:0') +def test_empty_device(): + tensor = TensorFlowCompBackend.empty((10, 3), device='CPU:0') + assert tensor.tensor.shape == (10, 3) + assert tensor.tensor.device.endswith('CPU:0') def test_squeeze(): - tensor = tf.zeros(shape=(1, 1, 3, 1)) + tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) squeezed = TensorFlowCompBackend.squeeze(tensor) - assert squeezed.shape == (3,) + assert squeezed.tensor.shape == (3,) @pytest.mark.parametrize( @@ -89,26 +94,27 @@ def test_squeeze(): ], ) def test_minmax_normalize(array, t_range, x_range, result): + array = TensorFlowTensor(array) output = TensorFlowCompBackend.minmax_normalize( tensor=array, t_range=t_range, x_range=x_range ) - assert np.allclose(output, result) + assert np.allclose(output.tensor, result) def test_reshape(): - tensor = tf.zeros((3, 224, 224)) + tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) - assert reshaped.shape == (224, 224, 3) + assert reshaped.tensor.shape == (224, 224, 3) def test_stack(): - t0 = tf.zeros((3, 224, 224)) - t1 = tf.ones((3, 224, 224)) + t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) + t1 = TensorFlowTensor(tf.ones((3, 224, 224))) stacked1 = TensorFlowCompBackend.stack([t0, t1], dim=0) - assert isinstance(stacked1, tf.Tensor) - assert stacked1.shape == (2, 3, 224, 224) + assert isinstance(stacked1, TensorFlowTensor) + assert stacked1.tensor.shape == (2, 3, 224, 224) stacked2 = TensorFlowCompBackend.stack([t0, t1], dim=-1) - assert isinstance(stacked2, tf.Tensor) - assert stacked2.shape == (3, 224, 224, 2) + assert isinstance(stacked2, TensorFlowTensor) + assert stacked2.tensor.shape == (3, 224, 224, 2) From 194ab9f642791029015868513fce212a17443ca3 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 17:07:07 +0100 Subject: [PATCH 09/70] docs: clean up Signed-off-by: anna-charlotte --- docarray/computation/abstract_numpy_based_backend.py | 5 ++++- docarray/computation/numpy_backend.py | 4 +--- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py index 94a5a4a4ec1..aec4cdcb82a 100644 --- a/docarray/computation/abstract_numpy_based_backend.py +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -1,4 +1,5 @@ import types +from abc import ABC from typing import Any, Callable, List, Optional, Tuple, TypeVar, Union import numpy as np @@ -8,18 +9,20 @@ T = TypeVar('T') -class AbstractNumpyBasedBackend(AbstractComputationalBackend[T]): +class AbstractNumpyBasedBackend(AbstractComputationalBackend[T], ABC): _module: types.ModuleType _norm_left: Callable _norm_right: Callable @classmethod def stack(cls, tensors: Union[List[T], Tuple[T]], dim: int = 0) -> T: + """Stack a list of tensors along a new axis.""" norm_right = [cls._norm_right(t) for t in tensors] return cls._norm_left(cls._module.stack(norm_right, axis=dim)) @classmethod def n_dim(cls, array: T) -> int: + """Get the number of the array dimensions.""" return cls._module.ndim(cls._norm_right(array)) @classmethod diff --git a/docarray/computation/numpy_backend.py b/docarray/computation/numpy_backend.py index 000a6636103..15145fd63ee 100644 --- a/docarray/computation/numpy_backend.py +++ b/docarray/computation/numpy_backend.py @@ -58,9 +58,7 @@ def to_numpy(cls, array: 'np.ndarray') -> 'np.ndarray': return array @classmethod - def none_value( - cls, - ) -> Any: + def none_value(cls) -> Any: """Provide a compatible value that represents None in numpy.""" return None From 6a2ecf1dc13c07dae1813322b2aee5c9d1d23f30 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 31 Jan 2023 17:09:03 +0100 Subject: [PATCH 10/70] fix: retrieval and add docstring Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 35 +++++++----- .../tensorflow_backend/test_retrieval.py | 53 ++++++++++--------- 2 files changed, 49 insertions(+), 39 deletions(-) diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index c9ba6c7e64f..c8a52dafc86 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -55,13 +55,13 @@ def to_numpy(cls, array: 'TensorFlowTensor') -> 'np.ndarray': return cls._norm_right(array).numpy() @classmethod - def none_value( - cls, - ) -> typing.Any: + def none_value(cls) -> typing.Any: + """Provide a compatible value that represents None in numpy.""" return tf.constant(float('nan')) @classmethod def to_device(cls, tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor': + """Move the tensor to the specified device.""" if cls.device(tensor) == device: return tensor else: @@ -70,14 +70,22 @@ def to_device(cls, tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor @classmethod def device(cls, tensor: 'TensorFlowTensor') -> Optional[str]: + """Return device on which the tensor is allocated.""" return cls._norm_right(tensor).device @classmethod def detach(cls, tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': + """ + Returns the tensor detached from its current graph. + + :param tensor: tensor to be detached + :return: a detached tensor with the same data. + """ return cls._norm_left(tf.stop_gradient(cls._norm_right(tensor))) @classmethod def dtype(cls, tensor: 'TensorFlowTensor') -> tf.dtypes: + """Get the data type of the tensor.""" return cls._norm_right(tensor).dtype @classmethod @@ -99,38 +107,39 @@ def minmax_normalize( normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) return cls._norm_left(tf.cast(normalized, tensor.tensor.dtype)) - class Retrieval(AbstractComputationalBackend.Retrieval[tf.Tensor]): + class Retrieval(AbstractComputationalBackend.Retrieval[TensorFlowTensor]): """ Abstract class for retrieval and ranking functionalities """ @staticmethod def top_k( - values: 'tf.Tensor', + values: 'TensorFlowTensor', k: int, descending: bool = False, device: Optional[str] = None, - ) -> Tuple['tf.Tensor', 'tf.Tensor']: + ) -> Tuple['TensorFlowTensor', 'TensorFlowTensor']: """ Retrieves the top k smallest values in `values`, and returns them alongside their indices in the input `values`. Can also be used to retrieve the top k largest values, by setting the `descending` flag. - :param values: Torch tensor of values to rank. + :param values: TensorFlowTensor of values to rank. Should be of shape (n_queries, n_values_per_query). Inputs of shape (n_values_per_query,) will be expanded to (1, n_values_per_query). :param k: number of values to retrieve :param descending: retrieve largest values instead of smallest values - :param device: the computational device to use, - can be either `cpu` or a `cuda` device. - :return: Tuple containing the retrieved values, and their indices. - Both ar of shape (n_queries, k) + :param device: the computational device to use. + :return: Tuple of TensorFlowTensors containing the retrieved values, and + their indices. Both are of shape (n_queries, k) """ + comp_be = TensorFlowCompBackend if device is not None: - values = values.to(device) + values = comp_be.to_device(values, device) + values = comp_be._norm_right(values) if len(values.shape) <= 1: values = tf.expand_dims(values, axis=0) @@ -147,7 +156,7 @@ def top_k( if not descending: res_values = -result.values - return res_values, res_indices + return comp_be._norm_left(res_values), comp_be._norm_left(res_indices) class Metrics(AbstractComputationalBackend.Metrics[tf.Tensor]): """ diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index e20831a4c04..9ec9c6aad0d 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -2,53 +2,54 @@ import tensorflow._api.v2.experimental.numpy as tnp from docarray.computation.tensorflow_backend import TensorFlowCompBackend +from docarray.typing import TensorFlowTensor def test_top_k_descending_false(): top_k = TensorFlowCompBackend.Retrieval.top_k - a = tf.constant([1, 4, 2, 7, 4, 9, 2]) + a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) vals, indices = top_k(a, 3, descending=False) - assert vals.shape == (1, 3) - assert indices.shape == (1, 3) - assert tnp.allclose(tnp.squeeze(vals), tf.constant([1, 2, 2])) - assert tnp.allclose(tnp.squeeze(indices), tf.constant([0, 2, 6])) or ( - tnp.allclose(tnp.squeeze.indices), + assert vals.tensor.shape == (1, 3) + assert indices.tensor.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([1, 2, 2])) + assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([0, 2, 6])) or ( + tnp.allclose(tnp.squeeze.indices.tensor), tf.constant([0, 6, 2]), ) - a = tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]]) + a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) vals, indices = top_k(a, 3, descending=False) - assert vals.shape == (2, 3) - assert indices.shape == (2, 3) - assert tnp.allclose(vals[0], tf.constant([1, 2, 2])) - assert tnp.allclose(indices[0], tf.constant([0, 2, 6])) or tnp.allclose( - indices[0], tf.constant([0, 6, 2]) + assert vals.tensor.shape == (2, 3) + assert indices.tensor.shape == (2, 3) + assert tnp.allclose(vals.tensor[0], tf.constant([1, 2, 2])) + assert tnp.allclose(indices.tensor[0], tf.constant([0, 2, 6])) or tnp.allclose( + indices.tensor[0], tf.constant([0, 6, 2]) ) - assert tnp.allclose(vals[1], tf.constant([2, 3, 4])) - assert tnp.allclose(indices[1], tf.constant([2, 4, 6])) + assert tnp.allclose(vals.tensor[1], tf.constant([2, 3, 4])) + assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) def test_top_k_descending_true(): top_k = TensorFlowCompBackend.Retrieval.top_k - a = tf.constant([1, 4, 2, 7, 4, 9, 2]) + a = TensorFlowTensor(tf.constant([1, 4, 2, 7, 4, 9, 2])) vals, indices = top_k(a, 3, descending=True) - assert vals.shape == (1, 3) - assert indices.shape == (1, 3) - assert tnp.allclose(tnp.squeeze(vals), tf.constant([9, 7, 4])) - assert tnp.allclose(tnp.squeeze(indices), tf.constant([5, 3, 1])) + assert vals.tensor.shape == (1, 3) + assert indices.tensor.shape == (1, 3) + assert tnp.allclose(tnp.squeeze(vals.tensor), tf.constant([9, 7, 4])) + assert tnp.allclose(tnp.squeeze(indices.tensor), tf.constant([5, 3, 1])) - a = tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]]) + a = TensorFlowTensor(tf.constant([[1, 4, 2, 7, 4, 9, 2], [11, 6, 2, 7, 3, 10, 4]])) vals, indices = top_k(a, 3, descending=True) - assert vals.shape == (2, 3) - assert indices.shape == (2, 3) + assert vals.tensor.shape == (2, 3) + assert indices.tensor.shape == (2, 3) - assert tnp.allclose(vals[0], tf.constant([9, 7, 4])) - assert tnp.allclose(indices[0], tf.constant([0, 2, 6])) + assert tnp.allclose(vals.tensor[0], tf.constant([9, 7, 4])) + assert tnp.allclose(indices.tensor[0], tf.constant([5, 3, 1])) - assert tnp.allclose(vals[1], tf.constant([11, 10, 7])) - assert tnp.allclose(indices[1], tf.constant([0, 5, 3])) + assert tnp.allclose(vals.tensor[1], tf.constant([11, 10, 7])) + assert tnp.allclose(indices.tensor[1], tf.constant([0, 5, 3])) From 056db70df5bc36892daf144e05258d8341e602b3 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 1 Feb 2023 11:36:50 +0100 Subject: [PATCH 11/70] fix: add cosine sim for tf backend matrics Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 37 ++++++++++++------- .../tensorflow_backend/test_metrics.py | 21 +++++++++++ 2 files changed, 44 insertions(+), 14 deletions(-) diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index c8a52dafc86..5669afedf40 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -29,7 +29,7 @@ def _unsqueeze_if_single_axis(*matrices: tf.Tensor) -> List[tf.Tensor]: def _unsqueeze_if_scalar(t: tf.Tensor): if len(t.shape) == 0: # avoid scalar output - t = t.unsqueeze(0) + t = tf.expand_dims(t, 0) return t @@ -158,18 +158,18 @@ def top_k( return comp_be._norm_left(res_values), comp_be._norm_left(res_indices) - class Metrics(AbstractComputationalBackend.Metrics[tf.Tensor]): + class Metrics(AbstractComputationalBackend.Metrics[TensorFlowTensor]): """ Abstract base class for metrics (distances and similarities). """ @staticmethod def cosine_sim( - x_mat: 'tf.Tensor', - y_mat: 'tf.Tensor', + x_mat: 'TensorFlowTensor', + y_mat: 'TensorFlowTensor', eps: float = 1e-7, device: Optional[str] = None, - ) -> 'tf.Tensor': + ) -> 'TensorFlowTensor': """Pairwise cosine similarities between all vectors in x_mat and y_mat. :param x_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the @@ -184,15 +184,24 @@ def cosine_sim( The index [i_x, i_y] contains the cosine distance between x_mat[i_x] and y_mat[i_y]. """ - if device is not None: - with tf.device(device): - x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) - - a_n, b_n = x_mat.norm(dim=1)[:, None], y_mat.norm(dim=1)[:, None] - a_norm = x_mat / tf.clamp(a_n, min=eps) - b_norm = y_mat / tf.clamp(b_n, min=eps) - sims = tf.mm(a_norm, b_norm.transpose(0, 1)).squeeze() - return _unsqueeze_if_scalar(sims) + x_mat: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) + y_mat: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + + with tf.device(device): + x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) + + a_n = tf.linalg.normalize(x_mat, axis=1)[1] + b_n = tf.linalg.normalize(y_mat, axis=1)[1] + a_norm = x_mat / tf.clip_by_value( + a_n, clip_value_min=eps, clip_value_max=tf.float32.max + ) + b_norm = y_mat / tf.clip_by_value( + b_n, clip_value_min=eps, clip_value_max=tf.float32.max + ) + sims = tf.squeeze(tf.linalg.matmul(a_norm, tf.transpose(b_norm))) + sims = _unsqueeze_if_scalar(sims) + + return TensorFlowCompBackend._norm_left(sims) @staticmethod def euclidean_dist( diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index e69de29bb2d..5257756165c 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -0,0 +1,21 @@ +import tensorflow as tf + +from docarray.computation.tensorflow_backend import TensorFlowCompBackend +from docarray.typing import TensorFlowTensor + +metrics = TensorFlowCompBackend.Metrics + + +def test_cosine_sim_tf(): + a = TensorFlowTensor(tf.random.normal((128,))) + b = TensorFlowTensor(tf.random.normal((128,))) + assert metrics.cosine_sim(a, b).tensor.shape == (1,) + assert metrics.cosine_sim(a, b).tensor == metrics.cosine_sim(b, a).tensor + tf.experimental.numpy.allclose(metrics.cosine_sim(a, a).tensor, tf.ones(1)) + + a = TensorFlowTensor(tf.random.normal((10, 3))) + b = TensorFlowTensor(tf.random.normal((5, 3))) + assert metrics.cosine_sim(a, b).tensor.shape == (10, 5) + assert metrics.cosine_sim(b, a).tensor.shape == (5, 10) + diag_dists = tf.linalg.diag(metrics.cosine_sim(b, b).tensor) # self-comparisons + tf.experimental.numpy.allclose(diag_dists, tf.ones(5)) From 6c35902185b8ff9cab077176d53655a24ea2db10 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 1 Feb 2023 14:59:28 +0100 Subject: [PATCH 12/70] fix: euclidean dist Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 32 +++++++++--- .../tensorflow_backend/test_metrics.py | 50 +++++++++++++++++++ 2 files changed, 74 insertions(+), 8 deletions(-) diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 5669afedf40..3f40bc11d0e 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -205,10 +205,10 @@ def cosine_sim( @staticmethod def euclidean_dist( - x_mat: 'tf.Tensor', - y_mat: 'tf.Tensor', + x_mat: 'TensorFlowTensor', + y_mat: 'TensorFlowTensor', device: Optional[str] = None, - ) -> 'tf.Tensor': + ) -> 'TensorFlowTensor': """Pairwise Euclidian distances between all vectors in x_mat and y_mat. :param x_mat: tensor of shape (n_vectors, n_dim), where n_vectors is the @@ -222,14 +222,25 @@ def euclidean_dist( The index [i_x, i_y] contains the euclidian distance between x_mat[i_x] and y_mat[i_y]. """ - ... + x_mat: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) + y_mat: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + + with tf.device(device): + x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) + + dists = tf.squeeze( + tf.norm(tf.subtract(x_mat, y_mat), axis=-1, ord='euclidean') + ) + dists = _unsqueeze_if_scalar(dists) + + return TensorFlowCompBackend._norm_left(dists) @staticmethod def sqeuclidean_dist( - x_mat: 'tf.Tensor', - y_mat: 'tf.Tensor', + x_mat: 'TensorFlowTensor', + y_mat: 'TensorFlowTensor', device: Optional[str] = None, - ) -> 'tf.Tensor': + ) -> 'TensorFlowTensor': """Pairwise Squared Euclidian distances between all vectors in x_mat and y_mat. @@ -246,4 +257,9 @@ def sqeuclidean_dist( The index [i_x, i_y] contains the euclidian distance between x_mat[i_x] and y_mat[i_y]. """ - ... + dists = TensorFlowCompBackend.Metrics.euclidean_dist(x_mat, y_mat) + squared: tf.Tensor = tf.math.square( + TensorFlowCompBackend._norm_right(dists) + ) + + return TensorFlowCompBackend._norm_left(squared) diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index 5257756165c..f7e193872c7 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -19,3 +19,53 @@ def test_cosine_sim_tf(): assert metrics.cosine_sim(b, a).tensor.shape == (5, 10) diag_dists = tf.linalg.diag(metrics.cosine_sim(b, b).tensor) # self-comparisons tf.experimental.numpy.allclose(diag_dists, tf.ones(5)) + + +def test_euclidean_dist_tf(): + a = TensorFlowTensor(tf.random.normal((128,))) + b = TensorFlowTensor(tf.random.normal((128,))) + assert metrics.euclidean_dist(a, b).tensor.shape == (1,) + assert metrics.euclidean_dist(a, b).tensor == metrics.euclidean_dist(b, a).tensor + tf.experimental.numpy.allclose(metrics.euclidean_dist(a, a).tensor, tf.zeros(1)) + + a = TensorFlowTensor(tf.zeros((1, 1))) + b = TensorFlowTensor(tf.ones((4, 1))) + assert metrics.euclidean_dist(a, b).tensor.shape == (4,) + tf.experimental.numpy.allclose( + metrics.euclidean_dist(a, b).tensor, metrics.euclidean_dist(b, a).tensor + ) + tf.experimental.numpy.allclose(metrics.euclidean_dist(a, a).tensor, tf.zeros(1)) + + a = TensorFlowTensor(tf.constant([0.0, 2.0, 0.0])) + b = TensorFlowTensor(tf.constant([0.0, 0.0, 2.0])) + desired_output_singleton: tf.Tensor = tf.math.sqrt( + tf.constant([2.0**2.0 + 2.0**2.0]) + ) + tf.experimental.numpy.allclose( + metrics.euclidean_dist(a, b).tensor, desired_output_singleton + ) + + a = TensorFlowTensor(tf.constant([[0.0, 2.0, 0.0], [0.0, 0.0, 2.0]])) + b = TensorFlowTensor(tf.constant([[0.0, 0.0, 2.0], [0.0, 2.0, 0.0]])) + desired_output_singleton = tf.constant([[2.828427, 0.0], [0.0, 2.828427]]) + tf.experimental.numpy.allclose( + metrics.euclidean_dist(a, b).tensor, desired_output_singleton + ) + + +def test_sqeuclidean_dist_torch(): + a = TensorFlowTensor(tf.random.normal((128,))) + b = TensorFlowTensor(tf.random.normal((128,))) + assert metrics.sqeuclidean_dist(a, b).tensor.shape == (1,) + tf.experimental.numpy.allclose( + metrics.sqeuclidean_dist(a, b).tensor, + metrics.euclidean_dist(a, b).tensor ** 2, + ) + + a = TensorFlowTensor(tf.random.normal((1, 1))) + b = TensorFlowTensor(tf.random.normal((4, 1))) + assert metrics.sqeuclidean_dist(b, a).tensor.shape == (4,) + tf.experimental.numpy.allclose( + metrics.sqeuclidean_dist(a, b).tensor, + metrics.euclidean_dist(a, b).tensor ** 2, + ) From 2abe11395dea59f955fd8ccf21635c87365747ed Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 1 Feb 2023 16:33:00 +0100 Subject: [PATCH 13/70] fix: add typevar to register proto Signed-off-by: anna-charlotte --- docarray/typing/proto_register.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/docarray/typing/proto_register.py b/docarray/typing/proto_register.py index 4a1fe77dad9..a878e572c40 100644 --- a/docarray/typing/proto_register.py +++ b/docarray/typing/proto_register.py @@ -1,13 +1,15 @@ -from typing import Callable, Dict, Type +from typing import Callable, Dict, Type, TypeVar from docarray.typing.abstract_type import AbstractType _PROTO_TYPE_NAME_TO_CLASS: Dict[str, Type[AbstractType]] = {} +T = TypeVar(name='T', bound='AbstractType') + def _register_proto( proto_type_name: str, -) -> Callable[[Type[AbstractType]], Type[AbstractType]]: +) -> Callable[[Type[T]], Type[T]]: """Register a new type to be used in the protobuf serialization. This will add the type key to the global registry of types key used in the proto @@ -34,7 +36,7 @@ class MyType(AbstractType): f'the key {proto_type_name} is already registered in the global registry' ) - def _register(cls: Type['AbstractType']) -> Type['AbstractType']: + def _register(cls: Type[T]) -> Type[T]: cls._proto_type_name = proto_type_name _PROTO_TYPE_NAME_TO_CLASS[proto_type_name] = cls From beb340e59d64d4b5bc3ba70e54695857194f64ef Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 1 Feb 2023 17:51:22 +0100 Subject: [PATCH 14/70] fix: clean up Signed-off-by: anna-charlotte --- docarray/computation/tensorflow_backend.py | 38 +++++++++++---------- docarray/typing/tensor/tensorflow_tensor.py | 10 ++++-- 2 files changed, 27 insertions(+), 21 deletions(-) diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 3f40bc11d0e..2053c0c8525 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -139,17 +139,19 @@ def top_k( if device is not None: values = comp_be.to_device(values, device) - values = comp_be._norm_right(values) - if len(values.shape) <= 1: - values = tf.expand_dims(values, axis=0) + tf_values: tf.Tensor = comp_be._norm_right(values) + if len(tf_values.shape) <= 1: + tf_values = tf.expand_dims(tf_values, axis=0) - len_values = values.shape[-1] if len(values.shape) > 1 else len(values) - k = min(k, len_values) + len_tf_values = ( + tf_values.shape[-1] if len(tf_values.shape) > 1 else len(tf_values) + ) + k = min(k, len_tf_values) if not descending: - values = -values + tf_values = -tf_values - result = tf.math.top_k(input=values, k=k, sorted=True) + result = tf.math.top_k(input=tf_values, k=k, sorted=True) res_values = result.values res_indices = result.indices @@ -184,18 +186,18 @@ def cosine_sim( The index [i_x, i_y] contains the cosine distance between x_mat[i_x] and y_mat[i_y]. """ - x_mat: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) - y_mat: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + x_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) + y_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) with tf.device(device): - x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) + x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) - a_n = tf.linalg.normalize(x_mat, axis=1)[1] - b_n = tf.linalg.normalize(y_mat, axis=1)[1] - a_norm = x_mat / tf.clip_by_value( + a_n = tf.linalg.normalize(x_mat_tf, axis=1)[1] + b_n = tf.linalg.normalize(y_mat_tf, axis=1)[1] + a_norm = x_mat_tf / tf.clip_by_value( a_n, clip_value_min=eps, clip_value_max=tf.float32.max ) - b_norm = y_mat / tf.clip_by_value( + b_norm = y_mat_tf / tf.clip_by_value( b_n, clip_value_min=eps, clip_value_max=tf.float32.max ) sims = tf.squeeze(tf.linalg.matmul(a_norm, tf.transpose(b_norm))) @@ -222,14 +224,14 @@ def euclidean_dist( The index [i_x, i_y] contains the euclidian distance between x_mat[i_x] and y_mat[i_y]. """ - x_mat: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) - y_mat: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + x_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) + y_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) with tf.device(device): - x_mat, y_mat = _unsqueeze_if_single_axis(x_mat, y_mat) + x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) dists = tf.squeeze( - tf.norm(tf.subtract(x_mat, y_mat), axis=-1, ord='euclidean') + tf.norm(tf.subtract(x_mat_tf, y_mat_tf), axis=-1, ord='euclidean') ) dists = _unsqueeze_if_scalar(dists) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index dee156217aa..7b9030fb2f3 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -1,4 +1,4 @@ -from typing import TYPE_CHECKING, Any, Dict, Generic, Type, TypeVar, Union +from typing import TYPE_CHECKING, Any, Dict, Generic, Type, TypeVar, Union, cast import numpy as np import tensorflow as tf # type: ignore @@ -21,6 +21,8 @@ node_base: type = type(BaseNode) +# the mypy error suppression below should not be necessary anymore once the following +# is released in mypy: https://github.com/python/mypy/pull/14135 class metaTensorFlow( AbstractTensor.__parametrized_meta__, # type: ignore node_base, # type: ignore @@ -52,7 +54,9 @@ def validate( field: 'ModelField', config: 'BaseConfig', ) -> T: - if isinstance(value, tf.Tensor): + if isinstance(value, TensorFlowTensor): + return cast(T, value) + elif isinstance(value, tf.Tensor): return cls(tensor=value) else: try: @@ -112,7 +116,7 @@ def from_ndarray(cls: Type[T], value: np.ndarray) -> T: """ return cls._docarray_from_native(tf.convert_to_tensor(value)) - def unwrap(self): + def unwrap(self) -> tf.Tensor: """ Return the original tensorflow.Tensor without any memory copy. From 1817c44f51990cea46a114e3d9185058ef04b129 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 08:56:18 +0100 Subject: [PATCH 15/70] fix: add tft to inits Signed-off-by: anna-charlotte --- docarray/typing/__init__.py | 9 +++++++++ docarray/typing/tensor/__init__.py | 9 +++++++++ 2 files changed, 18 insertions(+) diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index 8bf129f43d1..8ace63f9aa1 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -58,3 +58,12 @@ 'ImageTorchTensor', ] ) + +try: + import tensorflow as tf # noqa: F401 +except ImportError: + pass +else: + from docarray.typing.tensor import TensorFlowTensor # noqa: F401 + + __all__.extend(['TensorFlowTensor']) diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index 79b3a3371a5..3bdc4acb793 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -24,3 +24,12 @@ from docarray.typing.tensor.torch_tensor import TorchTensor # noqa: F401 __all__.extend(['TorchEmbedding', 'TorchTensor', 'ImageTorchTensor']) + +try: + import tensorflow as tf # noqa: F401 +except ImportError: + pass +else: + from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 + + __all__.extend(['TensorFlowTensor']) From a74daac403a643ce3f9278f27ecce96395e395db Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 09:56:30 +0100 Subject: [PATCH 16/70] test: add tests for tensorflow tensor Signed-off-by: anna-charlotte --- .../typing/tensor/test_tensor_flow_tensor.py | 60 ++++++++++++++++++- 1 file changed, 57 insertions(+), 3 deletions(-) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index b345ca7a6ef..0e75484d7c7 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -3,6 +3,7 @@ import tensorflow as tf from pydantic import schema_json_of from pydantic.tools import parse_obj_as +from tensorflow.python.framework.errors_impl import InvalidArgumentError from docarray.base_document.io.json import orjson_dumps from docarray.typing import TensorFlowTensor @@ -28,6 +29,13 @@ def test_unwrap(): assert np.allclose(unwrapped, np.zeros((3, 224, 224))) +def test_from_ndarray(): + nd = np.array([1, 2, 3]) + tensor = TensorFlowTensor.from_ndarray(nd) + assert isinstance(tensor, TensorFlowTensor) + assert isinstance(tensor.tensor, tf.Tensor) + + def test_parametrized(): # correct shape, single axis tf_tensor = parse_obj_as(TensorFlowTensor[128], tf.zeros(128)) @@ -44,12 +52,10 @@ def test_parametrized(): # wrong but reshapable shape tf_tensor = parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 3, 224))) assert isinstance(tf_tensor, TensorFlowTensor) - # assert isinstance(tf_tensor.tensor, tf.Tensor) + assert isinstance(tf_tensor.tensor, tf.Tensor) assert tf_tensor.tensor.shape == (3, 224, 224) # wrong and not reshapable shape - from tensorflow.python.framework.errors_impl import InvalidArgumentError - with pytest.raises(InvalidArgumentError): parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 224))) @@ -83,3 +89,51 @@ def test_parametrized_with_str(): with pytest.raises(ValueError): _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60))) + + +@pytest.mark.parametrize('shape', [(3, 224, 224), (224, 224, 3)]) +def test_parameterized_tensor_class_name(shape): + MyTFT = TensorFlowTensor[3, 224, 224] + tensor = parse_obj_as(MyTFT, tf.zeros(shape)) + + assert MyTFT.__name__ == 'TensorFlowTensor[3, 224, 224]' + assert MyTFT.__qualname__ == 'TensorFlowTensor[3, 224, 224]' + + assert tensor.__class__.__name__ == 'TensorFlowTensor' + assert tensor.__class__.__qualname__ == 'TensorFlowTensor' + assert f'{tensor.tensor[0][0][0]}' == '0.0' + + +def test_parametrized_subclass(): + c1 = TensorFlowTensor[128] + c2 = TensorFlowTensor[128] + assert issubclass(c1, c2) + assert issubclass(c1, TensorFlowTensor) + + assert not issubclass(c1, TensorFlowTensor[256]) + + +def test_parametrized_instance(): + t = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) + assert isinstance(t, TensorFlowTensor[128]) + assert isinstance(t, TensorFlowTensor) + # assert isinstance(t, tf.Tensor) + + assert not isinstance(t, TensorFlowTensor[256]) + assert not isinstance(t, TensorFlowTensor[2, 128]) + assert not isinstance(t, TensorFlowTensor[2, 2, 64]) + + +def test_parametrized_equality(): + t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) + t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) + assert tf.experimental.numpy.allclose(t1.tensor, t2.tensor) + + +def test_parametrized_operations(): + t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) + t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) + t_result = t1.tensor + t2.tensor + assert isinstance(t_result, tf.Tensor) + assert not isinstance(t_result, TensorFlowTensor) + assert not isinstance(t_result, TensorFlowTensor[128]) From ab7d15326f90261e1bcf28c3214400223a006aa9 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 10:15:06 +0100 Subject: [PATCH 17/70] fix: mypy checks Signed-off-by: anna-charlotte --- docarray/typing/__init__.py | 2 +- docarray/typing/proto_register.py | 2 +- docarray/typing/tensor/__init__.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index 8ace63f9aa1..def9249935d 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -60,7 +60,7 @@ ) try: - import tensorflow as tf # noqa: F401 + import tensorflow as tf # noqa: F401; type: ignore except ImportError: pass else: diff --git a/docarray/typing/proto_register.py b/docarray/typing/proto_register.py index a878e572c40..ff7dd1038dd 100644 --- a/docarray/typing/proto_register.py +++ b/docarray/typing/proto_register.py @@ -4,7 +4,7 @@ _PROTO_TYPE_NAME_TO_CLASS: Dict[str, Type[AbstractType]] = {} -T = TypeVar(name='T', bound='AbstractType') +T = TypeVar('T', bound='AbstractType') def _register_proto( diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index 3bdc4acb793..903821485c6 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -26,7 +26,7 @@ __all__.extend(['TorchEmbedding', 'TorchTensor', 'ImageTorchTensor']) try: - import tensorflow as tf # noqa: F401 + import tensorflow as tf # noqa: F401; type: ignore except ImportError: pass else: From 72744ad05cb9f9834d4913ec440c787688e762b1 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 10:15:21 +0100 Subject: [PATCH 18/70] fix: docarray from native Signed-off-by: anna-charlotte --- docarray/typing/tensor/tensorflow_tensor.py | 21 ++++++++++++++------- 1 file changed, 14 insertions(+), 7 deletions(-) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 7b9030fb2f3..8ae47bb556b 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -57,7 +57,7 @@ def validate( if isinstance(value, TensorFlowTensor): return cast(T, value) elif isinstance(value, tf.Tensor): - return cls(tensor=value) + return cls._docarray_from_native(value) else: try: arr: tf.Tensor = tf.constant(value) @@ -69,17 +69,24 @@ def validate( ) @classmethod - def _docarray_from_native(cls: Type[T], value: tf.Tensor) -> T: + def _docarray_from_native(cls: Type[T], value: Union[tf.Tensor, T]) -> T: """Create a TensorFlowTensor from a native tensorflow.Tensor :param value: the native tf.Tensor :return: a TensorFlowTensor """ - if cls.__unparametrizedcls__: # This is not None if the tensor is parametrized - cls_param = cls.__unparametrizedcls__ + if isinstance(value, TensorFlowTensor): + if cls.__unparametrizedcls__: # None if the tensor is parametrized + value.__class__ = cls.__unparametrizedcls__ + else: + value.__class__ = cls + return cast(T, value) else: - cls_param = cls - return cls_param(tensor=value) + if cls.__unparametrizedcls__: # None if the tensor is parametrized + cls_param = cls.__unparametrizedcls__ + else: + cls_param = cls + return cls_param(tensor=value) @staticmethod def get_comp_backend() -> 'TensorFlowCompBackend': @@ -114,7 +121,7 @@ def from_ndarray(cls: Type[T], value: np.ndarray) -> T: :param value: the numpy array :return: a TensorFlowTensor """ - return cls._docarray_from_native(tf.convert_to_tensor(value)) + return TensorFlowTensor(tf.convert_to_tensor(value)) def unwrap(self) -> tf.Tensor: """ From dfdff10860d53c13d4845af1298ca29b2a6a90ec Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 13:36:31 +0100 Subject: [PATCH 19/70] docs: add documentatino and clean up Signed-off-by: anna-charlotte --- .../abstract_numpy_based_backend.py | 7 ++ docarray/computation/tensorflow_backend.py | 11 ++- docarray/typing/__init__.py | 2 +- docarray/typing/tensor/__init__.py | 2 +- docarray/typing/tensor/tensorflow_tensor.py | 88 +++++++++++++++++-- 5 files changed, 100 insertions(+), 10 deletions(-) diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py index aec4cdcb82a..20fbc12b2fc 100644 --- a/docarray/computation/abstract_numpy_based_backend.py +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -11,6 +11,13 @@ class AbstractNumpyBasedBackend(AbstractComputationalBackend[T], ABC): _module: types.ModuleType + + # _norm_left() and _norm_right() are functions to transform the input/output + # from cls_A -> cls_B and back depending on the subclass. This is especially + # important for the TensorFlowTensor class: + # If a TensorFlowTensor instance is input to a function, we first want to + # transform it to a tf.Tensor, since the tf.Tensor is what the _module of + # AbstractNumpyBasedBackend works on. Vice versa for the output. _norm_left: Callable _norm_right: Callable diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 2053c0c8525..cc3cd3dbfcc 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -11,7 +11,8 @@ def _unsqueeze_if_single_axis(*matrices: tf.Tensor) -> List[tf.Tensor]: - """Unsqueezes tensors that only have one axis, at dim 0. + """ + Unsqueezes tensors that only have one axis, at dim 0. This ensures that all outputs can be treated as matrices, not vectors. :param matrices: Matrices to be unsqueezed @@ -27,7 +28,13 @@ def _unsqueeze_if_single_axis(*matrices: tf.Tensor) -> List[tf.Tensor]: return unsqueezed -def _unsqueeze_if_scalar(t: tf.Tensor): +def _unsqueeze_if_scalar(t: tf.Tensor) -> tf.Tensor: + """ + Unsqueezes tensor of a scalar, from shape () to shape (1,). + + :param t: tensor to unsqueeze. + :return: unsqueezed tf.Tensor + """ if len(t.shape) == 0: # avoid scalar output t = tf.expand_dims(t, 0) return t diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index def9249935d..f76b125f605 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -60,7 +60,7 @@ ) try: - import tensorflow as tf # noqa: F401; type: ignore + import tensorflow as tf # type: ignore # noqa: F401 except ImportError: pass else: diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index 903821485c6..ed0e3d2cd6b 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -26,7 +26,7 @@ __all__.extend(['TorchEmbedding', 'TorchTensor', 'ImageTorchTensor']) try: - import tensorflow as tf # noqa: F401; type: ignore + import tensorflow as tf # type: ignore # noqa: F401 except ImportError: pass else: diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 8ae47bb556b..9fc7117693c 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -33,6 +33,72 @@ class metaTensorFlow( @_register_proto(proto_type_name='tensorflow_tensor') class TensorFlowTensor(AbstractTensor, Generic[ShapeT], metaclass=metaTensorFlow): + """ + TensorFlowTensor class with a `.tensor` attribute of type `tf.Tensor`, intended for + use in a Document. + This enables (de)serialization from/to protobuf and json, data validation, + and coersion from compatible types like numpy.ndarray. + + This type can also be used in a parametrized way, specifying the shape of the + tensor. + + EXAMPLE USAGE + + .. code-block:: python + + from docarray import BaseDocument + from docarray.typing import TensorFlowTensor + import tensorflow as tf + + + class MyDoc(BaseDocument): + tensor: TensorFlowTensor + image_tensor: TensorFlowTensor[3, 224, 224] + square_crop: TensorFlowTensor[3, 'x', 'x'] + + + # create a document with tensors + doc = MyDoc( + tensor=tf.zeros((128,)), + image_tensor=tf.zeros((3, 224, 224)), + square_crop=tf.zeros((3, 64, 64)), + ) + + # automatic shape conversion + doc = MyDoc( + tensor=tf.zeros((128,)), + image_tensor=tf.zeros((224, 224, 3)), # will reshape to (3, 224, 224) + square_crop=tf.zeros((3, 128, 128)), + ) + + # !! The following will raise an error due to shape mismatch !! + doc = MyDoc( + tensor=tf.zeros((128,)), + image_tensor=tf.zeros((224, 224)), # this will fail validation + square_crop=tf.zeros((3, 128, 64)), # this will also fail validation + ) + + If you want to call functions provided by tensorflow you have to access the + `.tensor` attribute or call `.unwrap()` on your TensorFlowTensor instance: + + .. code-block:: python + from docarray.typing import TensorFlowTensor + import tensorflow as tf + + + t = TensorFlowTensor(tf.zeros((224, 224))) + + # tensorflow functions + broadcasted = tf.broadcast_to(t.tensor, (3, 224, 224)) + broadcasted = tf.broadcast_to(t.unwrap(), (3, 224, 224)) + broadcasted = tf.broadcast_to(t, (3, 224, 224)) # this will fail + + # tensorflow.Tensor methods: + arr = t.tensor.numpy() + arr = t.unwrap().numpy() + arr = t.numpy() # this will fail + + """ __parametrized_meta__ = metaTensorFlow @@ -70,9 +136,11 @@ def validate( @classmethod def _docarray_from_native(cls: Type[T], value: Union[tf.Tensor, T]) -> T: - """Create a TensorFlowTensor from a native tensorflow.Tensor + """ + Create a TensorFlowTensor from a tensorflow.Tensor or TensorFlowTensor + instance. - :param value: the native tf.Tensor + :param value: instance of tf.Tensor or TensorFlowTensor :return: a TensorFlowTensor """ if isinstance(value, TensorFlowTensor): @@ -108,11 +176,20 @@ def _docarray_to_json_compatible(self) -> np.ndarray: return self.unwrap().numpy() def to_protobuf(self) -> 'NdArrayProto': - pass + """ + Transform self into an NdArrayProto protobuf message. + """ + raise NotImplementedError @classmethod def from_protobuf(cls: Type[T], pb_msg: 'NdArrayProto') -> 'T': - pass + """ + Read ndarray from a proto msg. + :param pb_msg: + :return: a TensorFlowTensor + """ + + raise NotImplementedError @classmethod def from_ndarray(cls: Type[T], value: np.ndarray) -> T: @@ -121,7 +198,7 @@ def from_ndarray(cls: Type[T], value: np.ndarray) -> T: :param value: the numpy array :return: a TensorFlowTensor """ - return TensorFlowTensor(tf.convert_to_tensor(value)) + return cls._docarray_from_native(tf.convert_to_tensor(value)) def unwrap(self) -> tf.Tensor: """ @@ -140,7 +217,6 @@ def unwrap(self) -> tf.Tensor: # here t1 is a docarray TensorFlowTensor t2 = t.unwrap() # here t2 is a pure tf.Tensor but t1 is still a Docarray TensorFlowTensor - # But both share the same underlying memory :return: a tf.Tensor From 28a7291d0522f847d95b8dbabb12d96f99e55d6f Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 14:15:12 +0100 Subject: [PATCH 20/70] fix: clean up Signed-off-by: anna-charlotte --- .../abstract_numpy_based_backend.py | 8 ++- docarray/computation/numpy_backend.py | 3 +- docarray/computation/tensorflow_backend.py | 50 +++++++++++-------- tests/units/util/test_typing.py | 8 ++- 4 files changed, 43 insertions(+), 26 deletions(-) diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py index 20fbc12b2fc..de9208516a6 100644 --- a/docarray/computation/abstract_numpy_based_backend.py +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -10,8 +10,14 @@ class AbstractNumpyBasedBackend(AbstractComputationalBackend[T], ABC): - _module: types.ModuleType + """ + Abstract base class for computational backends that are based on numpy. + This includes numpy (np) itself and tensorflow.experimental.numpy (tnp). + The overlap of those two is gathered in this abstract backend. Other functions + should be defined in corresponding subclasses. + """ + _module: types.ModuleType # _norm_left() and _norm_right() are functions to transform the input/output # from cls_A -> cls_B and back depending on the subclass. This is especially # important for the TensorFlowTensor class: diff --git a/docarray/computation/numpy_backend.py b/docarray/computation/numpy_backend.py index 15145fd63ee..d50c1a1ce71 100644 --- a/docarray/computation/numpy_backend.py +++ b/docarray/computation/numpy_backend.py @@ -115,9 +115,8 @@ class Retrieval(AbstractComputationalBackend.Retrieval[np.ndarray]): Abstract class for retrieval and ranking functionalities """ - @classmethod + @staticmethod def top_k( - cls, values: 'np.ndarray', k: int, descending: bool = False, diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index cc3cd3dbfcc..9903747f1b2 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -193,24 +193,28 @@ def cosine_sim( The index [i_x, i_y] contains the cosine distance between x_mat[i_x] and y_mat[i_y]. """ - x_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) - y_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + comp_be = TensorFlowCompBackend + x_mat_tf: tf.Tensor = comp_be._norm_right(x_mat) + y_mat_tf: tf.Tensor = comp_be._norm_right(y_mat) with tf.device(device): - x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) + x_mat_tf = tf.identity(x_mat_tf) + y_mat_tf = tf.identity(y_mat_tf) + + x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) - a_n = tf.linalg.normalize(x_mat_tf, axis=1)[1] - b_n = tf.linalg.normalize(y_mat_tf, axis=1)[1] - a_norm = x_mat_tf / tf.clip_by_value( - a_n, clip_value_min=eps, clip_value_max=tf.float32.max - ) - b_norm = y_mat_tf / tf.clip_by_value( - b_n, clip_value_min=eps, clip_value_max=tf.float32.max - ) - sims = tf.squeeze(tf.linalg.matmul(a_norm, tf.transpose(b_norm))) - sims = _unsqueeze_if_scalar(sims) + a_n = tf.linalg.normalize(x_mat_tf, axis=1)[1] + b_n = tf.linalg.normalize(y_mat_tf, axis=1)[1] + a_norm = x_mat_tf / tf.clip_by_value( + a_n, clip_value_min=eps, clip_value_max=tf.float32.max + ) + b_norm = y_mat_tf / tf.clip_by_value( + b_n, clip_value_min=eps, clip_value_max=tf.float32.max + ) + sims = tf.squeeze(tf.linalg.matmul(a_norm, tf.transpose(b_norm))) + sims = _unsqueeze_if_scalar(sims) - return TensorFlowCompBackend._norm_left(sims) + return comp_be._norm_left(sims) @staticmethod def euclidean_dist( @@ -231,18 +235,20 @@ def euclidean_dist( The index [i_x, i_y] contains the euclidian distance between x_mat[i_x] and y_mat[i_y]. """ - x_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(x_mat) - y_mat_tf: tf.Tensor = TensorFlowCompBackend._norm_right(y_mat) + comp_be = TensorFlowCompBackend + x_mat_tf: tf.Tensor = comp_be._norm_right(x_mat) + y_mat_tf: tf.Tensor = comp_be._norm_right(y_mat) with tf.device(device): - x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) + x_mat_tf = tf.identity(x_mat_tf) + y_mat_tf = tf.identity(y_mat_tf) + + x_mat_tf, y_mat_tf = _unsqueeze_if_single_axis(x_mat_tf, y_mat_tf) - dists = tf.squeeze( - tf.norm(tf.subtract(x_mat_tf, y_mat_tf), axis=-1, ord='euclidean') - ) - dists = _unsqueeze_if_scalar(dists) + dists = tf.squeeze(tf.norm(tf.subtract(x_mat_tf, y_mat_tf), axis=-1)) + dists = _unsqueeze_if_scalar(dists) - return TensorFlowCompBackend._norm_left(dists) + return comp_be._norm_left(dists) @staticmethod def sqeuclidean_dist( diff --git a/tests/units/util/test_typing.py b/tests/units/util/test_typing.py index bcbed3fd9b1..aa21c1071d0 100644 --- a/tests/units/util/test_typing.py +++ b/tests/units/util/test_typing.py @@ -2,7 +2,7 @@ import pytest -from docarray.typing import NdArray, TorchTensor +from docarray.typing import NdArray, TensorFlowTensor, TorchTensor from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union, is_type_tensor @@ -11,9 +11,11 @@ 'type_, is_tensor', [ (int, False), + (TensorFlowTensor, True), (TorchTensor, True), (NdArray, True), (AbstractTensor, True), + (Optional[TensorFlowTensor], False), (Optional[TorchTensor], False), (Union[TorchTensor, NdArray], False), (None, False), @@ -28,13 +30,17 @@ def test_is_type_tensor(type_, is_tensor): 'type_, is_union_tensor', [ (int, False), + (TensorFlowTensor, False), (TorchTensor, False), (NdArray, False), + (Optional[TensorFlowTensor], True), (Optional[TorchTensor], True), (Optional[NdArray], True), (Union[NdArray, TorchTensor], True), + (Union[NdArray, TorchTensor, TensorFlowTensor], True), (Union[NdArray, TorchTensor, AbstractTensor], True), (Union[NdArray, TorchTensor, Optional[TorchTensor]], True), + (Union[NdArray, TorchTensor, Optional[TensorFlowTensor]], True), (Union[NdArray, TorchTensor, None], True), ], ) From 418ee3714325cb83dbf940e9f97c07a4bcd17fc6 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Thu, 2 Feb 2023 14:29:43 +0100 Subject: [PATCH 21/70] fix: clean up Signed-off-by: anna-charlotte --- tests/units/array/test_array.py | 8 +++++--- tests/units/typing/tensor/test_cross_backend.py | 10 +++++++++- 2 files changed, 14 insertions(+), 4 deletions(-) diff --git a/tests/units/array/test_array.py b/tests/units/array/test_array.py index aabbbe2c5e1..09efd08470d 100644 --- a/tests/units/array/test_array.py +++ b/tests/units/array/test_array.py @@ -5,7 +5,7 @@ import torch from docarray import BaseDocument, DocumentArray -from docarray.typing import NdArray, TorchTensor +from docarray.typing import NdArray, TensorFlowTensor, TorchTensor @pytest.fixture() @@ -211,9 +211,11 @@ class Mmdoc(BaseDocument): def test_get_bulk_attributes_union_type_nested(): class MyDoc(BaseDocument): embedding: Union[Optional[TorchTensor], Optional[NdArray]] - embedding2: Optional[Union[TorchTensor, NdArray]] + embedding2: Optional[Union[TorchTensor, NdArray, TensorFlowTensor]] embedding3: Optional[Optional[TorchTensor]] - embedding4: Union[Optional[Union[TorchTensor, NdArray]], TorchTensor] + embedding4: Union[ + Optional[Union[TorchTensor, NdArray, TensorFlowTensor]], TorchTensor + ] da = DocumentArray[MyDoc]( [ diff --git a/tests/units/typing/tensor/test_cross_backend.py b/tests/units/typing/tensor/test_cross_backend.py index b2e0ba6ec53..baefeb91683 100644 --- a/tests/units/typing/tensor/test_cross_backend.py +++ b/tests/units/typing/tensor/test_cross_backend.py @@ -1,14 +1,22 @@ import numpy as np from pydantic import parse_obj_as -from docarray.typing import NdArray, TorchTensor +from docarray.typing import NdArray, TensorFlowTensor, TorchTensor def test_coercion_behavior(): t_np = parse_obj_as(NdArray[128], np.zeros(128)) t_th = parse_obj_as(TorchTensor[128], np.zeros(128)) + t_tf = parse_obj_as(TensorFlowTensor[128], np.zeros(128)) assert isinstance(t_np, NdArray[128]) + assert not isinstance(t_np, TensorFlowTensor[128]) assert not isinstance(t_np, TorchTensor[128]) + assert isinstance(t_th, TorchTensor[128]) assert not isinstance(t_th, NdArray[128]) + assert not isinstance(t_th, TensorFlowTensor[128]) + + assert isinstance(t_tf, TensorFlowTensor[128]) + assert not isinstance(t_tf, TorchTensor[128]) + assert not isinstance(t_tf, NdArray[128]) From 217c870c8d605357a2c5683958d71433a8691788 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Fri, 3 Feb 2023 08:21:35 +0100 Subject: [PATCH 22/70] fix: stacked array with tf tensor Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 54 +++-- docarray/typing/tensor/tensor.py | 25 ++- tests/units/array/test_array_stacked.py | 2 +- tests/units/array/test_array_stacked_tf.py | 238 +++++++++++++++++++++ 4 files changed, 302 insertions(+), 17 deletions(-) create mode 100644 tests/units/array/test_array_stacked_tf.py diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index 1a1bb122a36..ec859fb3d0a 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -15,7 +15,7 @@ from docarray.array.abstract_array import AnyDocumentArray from docarray.array.array import DocumentArray from docarray.base_document import AnyDocument, BaseDocument -from docarray.typing import NdArray +from docarray.typing import NdArray, TensorFlowTensor from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union @@ -143,25 +143,41 @@ def _create_columns( for field, type_ in column_schema.items(): if issubclass(type_, AbstractTensor): tensor = getattr(docs[0], field) + is_tf_tensor = isinstance(tensor, TensorFlowTensor) + if is_tf_tensor: + tensor = tensor.tensor + column_shape = ( (len(docs), *tensor.shape) if tensor is not None else (len(docs),) ) - columns[field] = type_._docarray_from_native( - type_.get_comp_backend().empty( - column_shape, - dtype=tensor.dtype if hasattr(tensor, 'dtype') else None, - device=tensor.device if hasattr(tensor, 'device') else None, + if not is_tf_tensor: + columns[field] = type_._docarray_from_native( + type_.get_comp_backend().empty( + column_shape, + dtype=tensor.dtype if hasattr(tensor, 'dtype') else None, + device=tensor.device if hasattr(tensor, 'device') else None, + ) ) - ) + tf_stack = [] for i, doc in enumerate(docs): val = getattr(doc, field) if val is None: val = tensor_type.get_comp_backend().none_value() - cast(AbstractTensor, columns[field])[i] = val - setattr(doc, field, columns[field][i]) - del val + if is_tf_tensor: + tf_stack.append(val.tensor) + del val.tensor + else: + cast(AbstractTensor, columns[field])[i] = val + setattr(doc, field, columns[field][i]) # TODO in if: same + del val + + if is_tf_tensor: + import tensorflow as tf + + stacked: tf.Tensor = tf.stack(tf_stack) + columns[field] = TensorFlowTensor(stacked) elif issubclass(type_, BaseDocument): columns[field] = getattr(docs, field).stack() @@ -204,7 +220,11 @@ def __getitem__(self, item): # note this should handle slices doc = self._docs[item] # NOTE: this could be speed up by using a cache for field in self._columns.keys(): - setattr(doc, field, self._columns[field][item]) + if isinstance(self._columns[field], TensorFlowTensor): + c = self._columns[field].tensor[item] + else: + c = self._columns[field][item] + setattr(doc, field, c) return doc def _get_slice(self: T, item: slice) -> T: @@ -213,8 +233,13 @@ def _get_slice(self: T, item: slice) -> T: :param item: the slice to apply :return: a DocumentArrayStacked """ + columns_sliced = {} + for k, col in self._columns.items(): + if not isinstance(col[item], TensorFlowTensor): + columns_sliced[k] = TensorFlowTensor(col.tensor[item]) + else: + columns_sliced[k] = col[item] - columns_sliced = {k: col[item] for k, col in self._columns.items()} columns_sliced_ = cast(Dict[str, Union[AbstractTensor, T]], columns_sliced) return self._from_columns(self._docs[item], columns_sliced_) @@ -270,7 +295,10 @@ def unstack(self: T) -> DocumentArray: for i, doc in enumerate(self._docs): for field in self._columns.keys(): val = self._columns[field] - setattr(doc, field, val[i]) + if isinstance(val, TensorFlowTensor): + setattr(doc, field, val.tensor[i]) + else: + setattr(doc, field, val[i]) # NOTE: here we might need to copy the tensor # see here diff --git a/docarray/typing/tensor/tensor.py b/docarray/typing/tensor/tensor.py index 565cb26e5a6..ac9c361c242 100644 --- a/docarray/typing/tensor/tensor.py +++ b/docarray/typing/tensor/tensor.py @@ -4,10 +4,29 @@ try: import torch # noqa: F401 + + from docarray.typing.tensor.torch_tensor import TorchTensor # noqa: F401 + + is_torch_available = True except ImportError: AnyTensor = Union[NdArray] # type: ignore + is_torch_available = False -else: - from docarray.typing.tensor.torch_tensor import TorchTensor # noqa: F401 +try: + import tensorflow as tf # noqa: F401 - AnyTensor = Union[NdArray, TorchTensor] # type: ignore + from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 + + is_tf_available = True +except ImportError: + is_tf_available = False + + +if is_torch_available and is_tf_available: + AnyTensor = Union[NdArray, TorchTensor, TensorFlowTensor] +elif is_torch_available: + AnyTensor = Union[NdArray, TorchTensor] +elif is_tf_available: + AnyTensor = Union[NdArray, TensorFlowTensor] +else: + AnyTensor = Union[NdArray] diff --git a/tests/units/array/test_array_stacked.py b/tests/units/array/test_array_stacked.py index b67ea0df9e6..70e7237aed9 100644 --- a/tests/units/array/test_array_stacked.py +++ b/tests/units/array/test_array_stacked.py @@ -28,7 +28,7 @@ def test_len(batch): def test_getitem(batch): for i in range(len(batch)): - assert (batch[i].tensor == torch.zeros(3, 224, 224)).all() + assert (batch[i].tensor.tensor == torch.zeros(3, 224, 224)).all() def test_iterator(batch): diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py new file mode 100644 index 00000000000..e6dc3507dd6 --- /dev/null +++ b/tests/units/array/test_array_stacked_tf.py @@ -0,0 +1,238 @@ +from typing import Optional, Union + +import pytest +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp + +from docarray import BaseDocument, DocumentArray +from docarray.array import DocumentArrayStacked +from docarray.typing import AnyTensor, NdArray, TensorFlowTensor + + +@pytest.fixture() +def batch(): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + import tensorflow as tf + + batch = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + + return batch.stack() + + +def test_len(batch): + assert len(batch) == 10 + + +def test_getitem(batch): + for i in range(len(batch)): + assert tnp.allclose(batch[i].tensor.tensor, tf.zeros((3, 224, 224))) + + +def test_iterator(batch): + for doc in batch: + assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) + + +def test_stack_setter(batch): + + batch.tensor = tf.ones((10, 3, 224, 224)) + + assert tnp.allclose(batch.tensor, tf.ones((10, 3, 224, 224))) + + +def test_stack_optional(batch): + + assert tnp.allclose(batch._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224))) + assert tnp.allclose(batch.tensor.tensor, tf.zeros((10, 3, 224, 224))) + + +def test_stack_mod_nested_document(): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + class MMdoc(BaseDocument): + img: Image + + batch = DocumentArray[MMdoc]( + [MMdoc(img=Image(tensor=tf.zeros((3, 224, 224)))) for _ in range(10)] + ) + + batch = batch.stack() + + assert tnp.allclose( + batch._columns['img']._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224)) + ) + + assert tnp.allclose(batch.img.tensor.tensor, tf.zeros((10, 3, 224, 224))) + + +def test_convert_to_da(batch): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + batch = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + + batch = batch.stack() + da = batch.unstack() + + for doc in da: + assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) + + +def test_unstack_nested_document(): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + class MMdoc(BaseDocument): + img: Image + + batch = DocumentArray[MMdoc]( + [MMdoc(img=Image(tensor=tf.zeros((3, 224, 224)))) for _ in range(10)] + ) + + batch = batch.stack() + da = batch.unstack() + + for doc in da: + assert tnp.allclose(doc.img.tensor.tensor, tf.zeros((3, 224, 224))) + + +def test_stack_call(): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + da = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + + da = da.stack() + + assert len(da) == 10 + + assert da.tensor.tensor.shape == (10, 3, 224, 224) + + +def test_context_manager(): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + da = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + + with da.stacked_mode() as da: + assert len(da) == 10 + + assert da.tensor.tensor.shape == ((10, 3, 224, 224)) + + da.tensor = tf.ones((10, 3, 224, 224)) + + tensor = da.tensor + + assert isinstance(tensor, list) + for doc in da: + assert tnp.allclose(doc.tensor.tensor, tf.ones((3, 224, 224))) + + +def test_stack_union(): + class Image(BaseDocument): + tensor: Union[NdArray[3, 224, 224], TensorFlowTensor[3, 224, 224]] + + batch = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + batch[3].tensor = tf.zeros((3, 224, 224)) + + # union fields aren't actually stacked + # just checking that there is no error + batch.stack() + + +@pytest.mark.parametrize( + 'tensor_type,tensor', + [(TensorFlowTensor, tf.zeros((3, 224, 224)))], +) +def test_any_tensor_with_tf(tensor_type, tensor): + class Image(BaseDocument): + tensor: AnyTensor + + da = DocumentArray[Image]( + [Image(tensor=tensor) for _ in range(10)], + tensor_type=tensor_type, + ).stack() + + for i in range(len(da)): + assert tnp.allclose(da[i].tensor.tensor, tensor) + + assert 'tensor' in da._columns.keys() + assert isinstance(da._columns['tensor'], tensor_type) + + +def test_any_tensor_with_optional(): + tensor = tf.zeros((3, 224, 224)) + + class Image(BaseDocument): + tensor: Optional[AnyTensor] + + class TopDoc(BaseDocument): + img: Image + + da = DocumentArray[TopDoc]( + [TopDoc(img=Image(tensor=tensor)) for _ in range(10)], + tensor_type=TensorFlowTensor, + ).stack() + + for i in range(len(da)): + assert tnp.allclose(da.img[i].tensor.tensor, tensor) + + assert 'tensor' in da.img._columns.keys() + assert isinstance(da.img._columns['tensor'], TensorFlowTensor) + assert isinstance(da.img._columns['tensor'].tensor, tf.Tensor) + + +def test_get_from_slice_stacked(): + class Doc(BaseDocument): + text: str + tensor: TensorFlowTensor + + da = DocumentArray[Doc]( + [Doc(text=f'hello{i}', tensor=tf.zeros((3, 224, 224))) for i in range(10)] + ).stack() + + da_sliced = da[0:10:2] + assert isinstance(da_sliced, DocumentArrayStacked) + + tensors = da_sliced.tensor.tensor + assert tensors.shape == (5, 3, 224, 224) + + +@pytest.mark.parametrize('tensor_backend', [TensorFlowTensor]) +def test_stack_none(tensor_backend): + class MyDoc(BaseDocument): + tensor: Optional[AnyTensor] + + da = DocumentArray[MyDoc]( + [MyDoc(tensor=None) for _ in range(10)], tensor_type=tensor_backend + ).stack() + + assert 'tensor' in da._columns.keys() + + +def test_keep_dtype_tf(): + class MyDoc(BaseDocument): + tensor: TensorFlowTensor + + da = DocumentArray[MyDoc]( + [MyDoc(tensor=tf.zeros([2, 4], dtype=tf.int32)) for _ in range(3)] + ) + assert da[0].tensor.tensor.dtype == tf.int32 + + da = da.stack() + assert da[0].tensor.tensor.dtype == tf.int32 + assert da.tensor.tensor.dtype == tf.int32 From fd7a8e57d10aa2a0be9366ec190ff43b72c4458b Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Fri, 3 Feb 2023 12:00:56 +0100 Subject: [PATCH 23/70] fix: stack with tftensor Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 55 ++++++++++++++++++--------------- 1 file changed, 30 insertions(+), 25 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index ec859fb3d0a..66fe3339645 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -33,6 +33,11 @@ except ImportError: TorchTensor = None # type: ignore +try: + import tensorflow as tf +except ImportError: + pass + T = TypeVar('T', bound='DocumentArrayStacked') @@ -141,43 +146,43 @@ def _create_columns( columns: Dict[str, Union[DocumentArrayStacked, AbstractTensor]] = dict() for field, type_ in column_schema.items(): - if issubclass(type_, AbstractTensor): + if isinstance(getattr(docs[0], field), TensorFlowTensor): + tf_stack = [] + for i, doc in enumerate(docs): + val = getattr(doc, field) + if val is None: + val = tensor_type.get_comp_backend().none_value() + tf_stack.append(val.tensor) + del val.tensor + + stacked: tf.Tensor = tf.stack(tf_stack) + columns[field] = TensorFlowTensor(stacked) + for i, doc in enumerate(docs): + val = getattr(doc, field) + val.tensor = columns[field] + + elif issubclass(type_, AbstractTensor): tensor = getattr(docs[0], field) - is_tf_tensor = isinstance(tensor, TensorFlowTensor) - if is_tf_tensor: - tensor = tensor.tensor column_shape = ( (len(docs), *tensor.shape) if tensor is not None else (len(docs),) ) - if not is_tf_tensor: - columns[field] = type_._docarray_from_native( - type_.get_comp_backend().empty( - column_shape, - dtype=tensor.dtype if hasattr(tensor, 'dtype') else None, - device=tensor.device if hasattr(tensor, 'device') else None, - ) + columns[field] = type_._docarray_from_native( + type_.get_comp_backend().empty( + column_shape, + dtype=tensor.dtype if hasattr(tensor, 'dtype') else None, + device=tensor.device if hasattr(tensor, 'device') else None, ) + ) - tf_stack = [] for i, doc in enumerate(docs): val = getattr(doc, field) if val is None: val = tensor_type.get_comp_backend().none_value() - if is_tf_tensor: - tf_stack.append(val.tensor) - del val.tensor - else: - cast(AbstractTensor, columns[field])[i] = val - setattr(doc, field, columns[field][i]) # TODO in if: same - del val - - if is_tf_tensor: - import tensorflow as tf - - stacked: tf.Tensor = tf.stack(tf_stack) - columns[field] = TensorFlowTensor(stacked) + cast(AbstractTensor, columns[field])[i] = val + setattr(doc, field, columns[field][i]) + del val elif issubclass(type_, BaseDocument): columns[field] = getattr(docs, field).stack() From 26150b6422e4aa54a5f524529935d5e55d2a6e1a Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Fri, 3 Feb 2023 12:06:37 +0100 Subject: [PATCH 24/70] test: fix get item test Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 3 +-- tests/units/array/test_array_stacked.py | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index 66fe3339645..c7139203f57 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -163,7 +163,6 @@ def _create_columns( elif issubclass(type_, AbstractTensor): tensor = getattr(docs[0], field) - column_shape = ( (len(docs), *tensor.shape) if tensor is not None else (len(docs),) ) @@ -240,7 +239,7 @@ def _get_slice(self: T, item: slice) -> T: """ columns_sliced = {} for k, col in self._columns.items(): - if not isinstance(col[item], TensorFlowTensor): + if isinstance(col[item], TensorFlowTensor): columns_sliced[k] = TensorFlowTensor(col.tensor[item]) else: columns_sliced[k] = col[item] diff --git a/tests/units/array/test_array_stacked.py b/tests/units/array/test_array_stacked.py index 70e7237aed9..b67ea0df9e6 100644 --- a/tests/units/array/test_array_stacked.py +++ b/tests/units/array/test_array_stacked.py @@ -28,7 +28,7 @@ def test_len(batch): def test_getitem(batch): for i in range(len(batch)): - assert (batch[i].tensor.tensor == torch.zeros(3, 224, 224)).all() + assert (batch[i].tensor == torch.zeros(3, 224, 224)).all() def test_iterator(batch): From 567b56a4a3baff25b20c335be3480f3d17b710c5 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Fri, 3 Feb 2023 14:29:54 +0100 Subject: [PATCH 25/70] fix: access by slice for tftensor Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 10 +++++----- tests/units/array/test_array_stacked_tf.py | 22 ++++++++++++++-------- 2 files changed, 19 insertions(+), 13 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index c7139203f57..6d88e8da9fb 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -159,7 +159,7 @@ def _create_columns( columns[field] = TensorFlowTensor(stacked) for i, doc in enumerate(docs): val = getattr(doc, field) - val.tensor = columns[field] + val.tensor = columns[field][i] elif issubclass(type_, AbstractTensor): tensor = getattr(docs[0], field) @@ -225,10 +225,10 @@ def __getitem__(self, item): # note this should handle slices # NOTE: this could be speed up by using a cache for field in self._columns.keys(): if isinstance(self._columns[field], TensorFlowTensor): - c = self._columns[field].tensor[item] + val = self._columns[field].tensor[item] else: - c = self._columns[field][item] - setattr(doc, field, c) + val = self._columns[field][item] + setattr(doc, field, val) return doc def _get_slice(self: T, item: slice) -> T: @@ -239,7 +239,7 @@ def _get_slice(self: T, item: slice) -> T: """ columns_sliced = {} for k, col in self._columns.items(): - if isinstance(col[item], TensorFlowTensor): + if isinstance(col, TensorFlowTensor): columns_sliced[k] = TensorFlowTensor(col.tensor[item]) else: columns_sliced[k] = col[item] diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index e6dc3507dd6..ffe70a00f50 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -44,6 +44,20 @@ def test_stack_setter(batch): assert tnp.allclose(batch.tensor, tf.ones((10, 3, 224, 224))) +def test_set_after_stacking(batch): + class Image(BaseDocument): + tensor: TensorFlowTensor[3, 224, 224] + + batch = DocumentArray[Image]( + [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] + ) + + batch = batch.stack() + batch.tensor.tensor = tf.ones((10, 3, 224, 224)) + for i, doc in enumerate(batch): + assert tnp.allclose(doc.tensor.tensor, batch.tensor.tensor[i]) + + def test_stack_optional(batch): assert tnp.allclose(batch._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224))) @@ -71,14 +85,6 @@ class MMdoc(BaseDocument): def test_convert_to_da(batch): - class Image(BaseDocument): - tensor: TensorFlowTensor[3, 224, 224] - - batch = DocumentArray[Image]( - [Image(tensor=tf.zeros((3, 224, 224))) for _ in range(10)] - ) - - batch = batch.stack() da = batch.unstack() for doc in da: From 665f40822230d506cf8aaba38fedbe49e7759d14 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 12:42:53 +0100 Subject: [PATCH 26/70] fix: add proto for tf Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 3 ++ docarray/array/array_stacked.py | 22 +++++----- docarray/typing/__init__.py | 3 +- docarray/typing/tensor/__init__.py | 3 +- docarray/typing/tensor/tensor.py | 11 +++-- docarray/typing/tensor/tensorflow_tensor.py | 24 +++++++++-- docarray/typing/tensor/torch_tensor.py | 1 - tests/integrations/typing/test_tensor.py | 10 ++++- .../typing/test_tensorflow_tensor.py | 16 ++++++++ .../integrations/typing/test_typing_proto.py | 40 +++++++++++++++++++ .../document/proto/test_proto_based_object.py | 3 ++ .../units/typing/tensor/test_audio_tensor.py | 1 + tests/units/typing/tensor/test_embedding.py | 2 + tests/units/typing/tensor/test_tensor.py | 1 + .../typing/tensor/test_tensor_flow_tensor.py | 29 ++++++++++++-- .../units/typing/tensor/test_torch_tensor.py | 1 + tests/units/typing/url/test_image_url.py | 1 + tests/units/typing/url/test_mesh_url.py | 1 + .../units/typing/url/test_point_cloud_url.py | 1 + 19 files changed, 144 insertions(+), 29 deletions(-) create mode 100644 tests/integrations/typing/test_tensorflow_tensor.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index a9e3394fe74..3823d7e473f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -58,6 +58,7 @@ jobs: run: | python -m pip install --upgrade pip python -m pip install poetry + pip install tensorflow==2.11.0 poetry install --without dev - name: Test basic import run: poetry run python -c 'from docarray import DocumentArray, BaseDocument' @@ -111,6 +112,7 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --all-extras + pip install tensorflow==2.11.0 - name: Test id: test @@ -182,6 +184,7 @@ jobs: python -m pip install poetry poetry install --all-extras pip install protobuf==3.19.0 # we check that we support 3.19 + pip install tensorflow==2.11.0 - name: Test id: test diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index 6d88e8da9fb..ffba747dbbd 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -15,7 +15,6 @@ from docarray.array.abstract_array import AnyDocumentArray from docarray.array.array import DocumentArray from docarray.base_document import AnyDocument, BaseDocument -from docarray.typing import NdArray, TensorFlowTensor from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union @@ -24,18 +23,18 @@ from pydantic.fields import ModelField from docarray.proto import DocumentArrayStackedProto - from docarray.typing import TorchTensor - from docarray.typing.tensor.abstract_tensor import AbstractTensor try: - from docarray.typing import TorchTensor + from docarray.typing import AnyTensor, TorchTensor except ImportError: TorchTensor = None # type: ignore try: - import tensorflow as tf -except ImportError: + import tensorflow as tf # type: ignore + + from docarray.typing import NdArray, TensorFlowTensor +except (ImportError, TypeError): pass T = TypeVar('T', bound='DocumentArrayStacked') @@ -224,11 +223,12 @@ def __getitem__(self, item): # note this should handle slices doc = self._docs[item] # NOTE: this could be speed up by using a cache for field in self._columns.keys(): - if isinstance(self._columns[field], TensorFlowTensor): - val = self._columns[field].tensor[item] + value = self._columns[field] + if isinstance(value, TensorFlowTensor): + new_value = value.tensor[item] else: - val = self._columns[field][item] - setattr(doc, field, val) + new_value = value[item] + setattr(doc, field, new_value) return doc def _get_slice(self: T, item: slice) -> T: @@ -237,7 +237,7 @@ def _get_slice(self: T, item: slice) -> T: :param item: the slice to apply :return: a DocumentArrayStacked """ - columns_sliced = {} + columns_sliced: Dict[str, AnyTensor] = {} for k, col in self._columns.items(): if isinstance(col, TensorFlowTensor): columns_sliced[k] = TensorFlowTensor(col.tensor[item]) diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index f76b125f605..29292965509 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -5,7 +5,6 @@ from docarray.typing.tensor.embedding.embedding import AnyEmbedding, NdArrayEmbedding from docarray.typing.tensor.ndarray import NdArray from docarray.typing.tensor.tensor import AnyTensor -from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor from docarray.typing.tensor.video import VideoNdArray from docarray.typing.url import ( AnyUrl, @@ -61,7 +60,7 @@ try: import tensorflow as tf # type: ignore # noqa: F401 -except ImportError: +except (ImportError, TypeError): pass else: from docarray.typing.tensor import TensorFlowTensor # noqa: F401 diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index ed0e3d2cd6b..fbd4e0b24ba 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -2,7 +2,6 @@ from docarray.typing.tensor.image import ImageNdArray, ImageTensor from docarray.typing.tensor.ndarray import NdArray from docarray.typing.tensor.tensor import AnyTensor -from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor __all__ = [ 'NdArray', @@ -27,7 +26,7 @@ try: import tensorflow as tf # type: ignore # noqa: F401 -except ImportError: +except (ImportError, TypeError): pass else: from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 diff --git a/docarray/typing/tensor/tensor.py b/docarray/typing/tensor/tensor.py index ac9c361c242..9d46e08a408 100644 --- a/docarray/typing/tensor/tensor.py +++ b/docarray/typing/tensor/tensor.py @@ -9,24 +9,23 @@ is_torch_available = True except ImportError: - AnyTensor = Union[NdArray] # type: ignore is_torch_available = False try: - import tensorflow as tf # noqa: F401 + import tensorflow as tf # type: ignore # noqa: F401 from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 is_tf_available = True -except ImportError: +except (ImportError, TypeError): is_tf_available = False if is_torch_available and is_tf_available: AnyTensor = Union[NdArray, TorchTensor, TensorFlowTensor] elif is_torch_available: - AnyTensor = Union[NdArray, TorchTensor] + AnyTensor = Union[NdArray, TorchTensor] # type: ignore elif is_tf_available: - AnyTensor = Union[NdArray, TensorFlowTensor] + AnyTensor = Union[NdArray, TensorFlowTensor] # type: ignore else: - AnyTensor = Union[NdArray] + AnyTensor = Union[NdArray] # type: ignore diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 9fc7117693c..0d558d59fe1 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -179,7 +179,17 @@ def to_protobuf(self) -> 'NdArrayProto': """ Transform self into an NdArrayProto protobuf message. """ - raise NotImplementedError + from docarray.proto import NdArrayProto + + nd_proto = NdArrayProto() + + value_np = self.tensor.numpy() + nd_proto.dense.buffer = value_np.tobytes() + nd_proto.dense.ClearField('shape') + nd_proto.dense.shape.extend(list(value_np.shape)) + nd_proto.dense.dtype = value_np.dtype.str + + return nd_proto @classmethod def from_protobuf(cls: Type[T], pb_msg: 'NdArrayProto') -> 'T': @@ -188,8 +198,16 @@ def from_protobuf(cls: Type[T], pb_msg: 'NdArrayProto') -> 'T': :param pb_msg: :return: a TensorFlowTensor """ - - raise NotImplementedError + source = pb_msg.dense + if source.buffer: + x = np.frombuffer(bytearray(source.buffer), dtype=source.dtype) + return cls.from_ndarray(x.reshape(source.shape)) + elif len(source.shape) > 0: + return cls.from_ndarray(np.zeros(source.shape)) + else: + raise ValueError( + f'Proto message {pb_msg} cannot be cast to a TensorFlowTensor.' + ) @classmethod def from_ndarray(cls: Type[T], value: np.ndarray) -> T: diff --git a/docarray/typing/tensor/torch_tensor.py b/docarray/typing/tensor/torch_tensor.py index c171024bf60..53bfb50a87c 100644 --- a/docarray/typing/tensor/torch_tensor.py +++ b/docarray/typing/tensor/torch_tensor.py @@ -10,7 +10,6 @@ if TYPE_CHECKING: from pydantic.fields import ModelField from pydantic import BaseConfig - import numpy as np from docarray.proto import NdArrayProto from docarray.computation.torch_backend import TorchCompBackend diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index 397bce00387..2c0cff23ee8 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -1,8 +1,10 @@ import numpy as np +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp # type: ignore import torch from docarray import BaseDocument -from docarray.typing import AnyTensor, NdArray, TorchTensor +from docarray.typing import AnyTensor, NdArray, TensorFlowTensor, TorchTensor def test_set_tensor(): @@ -20,3 +22,9 @@ class MyDocument(BaseDocument): assert isinstance(d.tensor, TorchTensor) assert isinstance(d.tensor, torch.Tensor) assert (d.tensor == torch.zeros((3, 224, 224))).all() + + d = MyDocument(tensor=tf.zeros((3, 224, 224))) + + assert isinstance(d.tensor, TensorFlowTensor) + assert isinstance(d.tensor.tensor, tf.Tensor) + assert tnp.allclose(d.tensor.tensor, tf.zeros((3, 224, 224))) diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py new file mode 100644 index 00000000000..bb403de1173 --- /dev/null +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -0,0 +1,16 @@ +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp # type: ignore + +from docarray import BaseDocument +from docarray.typing import TensorFlowTensor + + +def test_set_tensorflow_tensor(): + class MyDocument(BaseDocument): + t: TensorFlowTensor + + doc = MyDocument(t=tf.zeros((3, 224, 224))) + + assert isinstance(doc.t, TensorFlowTensor) + assert isinstance(doc.t.tensor, tf.Tensor) + assert tnp.allclose(doc.t.tensor, tf.zeros((3, 224, 224))) diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index 4aa88020c3f..dd4b2ef9dc2 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -1,4 +1,5 @@ import numpy as np +import pytest import torch from docarray import BaseDocument @@ -10,11 +11,13 @@ Mesh3DUrl, NdArray, PointCloud3DUrl, + TensorFlowTensor, TextUrl, TorchTensor, ) +@pytest.mark.proto def test_proto_all_types(): class Mymmdoc(BaseDocument): tensor: NdArray @@ -45,3 +48,40 @@ class Mymmdoc(BaseDocument): assert isinstance(value, np.ndarray) or isinstance(value, torch.Tensor) else: assert isinstance(value, doc._get_field_type(field)) + + +@pytest.mark.proto +def test_proto_all_types_proto3(): + import tensorflow as tf + + class Mymmdoc(BaseDocument): + tensor: NdArray + torch_tensor: TorchTensor + tf_tensor: TensorFlowTensor + embedding: AnyEmbedding + any_url: AnyUrl + image_url: ImageUrl + text_url: TextUrl + mesh_url: Mesh3DUrl + point_cloud_url: PointCloud3DUrl + + doc = Mymmdoc( + tensor=np.zeros((3, 224, 224)), + torch_tensor=torch.zeros((3, 224, 224)), + tf_tensor=tf.zeros((3, 224, 224)), + embedding=np.zeros((100, 1)), + any_url='http://jina.ai', + image_url='http://jina.ai/bla.jpg', + text_url='http://jina.ai', + mesh_url='http://jina.ai/mesh.obj', + point_cloud_url='http://jina.ai/mesh.obj', + ) + + new_doc = AnyDocument.from_protobuf(doc.to_protobuf()) + + for field, value in new_doc: + if field == 'embedding': + # embedding is a Union type, not supported by isinstance + assert isinstance(value, np.ndarray) or isinstance(value, torch.Tensor) + else: + assert isinstance(value, doc._get_field_type(field)) diff --git a/tests/units/document/proto/test_proto_based_object.py b/tests/units/document/proto/test_proto_based_object.py index 6d2b7a79b7b..ecec88fb6e6 100644 --- a/tests/units/document/proto/test_proto_based_object.py +++ b/tests/units/document/proto/test_proto_based_object.py @@ -1,9 +1,11 @@ import numpy as np +import pytest from docarray.proto import DocumentProto, NodeProto from docarray.typing import NdArray +@pytest.mark.proto def test_ndarray(): original_ndarray = np.zeros((3, 224, 224)) @@ -15,6 +17,7 @@ def test_ndarray(): assert (tensor == original_ndarray).all() +@pytest.mark.proto def test_document_proto_set(): data = {} diff --git a/tests/units/typing/tensor/test_audio_tensor.py b/tests/units/typing/tensor/test_audio_tensor.py index 9a2bf64fa69..341c226b35d 100644 --- a/tests/units/typing/tensor/test_audio_tensor.py +++ b/tests/units/typing/tensor/test_audio_tensor.py @@ -54,6 +54,7 @@ def test_illegal_validation(cls_tensor, tensor): parse_obj_as(cls_tensor, tensor) +@pytest.mark.proto @pytest.mark.parametrize( 'cls_tensor,tensor,proto_key', [ diff --git a/tests/units/typing/tensor/test_embedding.py b/tests/units/typing/tensor/test_embedding.py index 447351c543c..f7eebcf4caf 100644 --- a/tests/units/typing/tensor/test_embedding.py +++ b/tests/units/typing/tensor/test_embedding.py @@ -1,10 +1,12 @@ import numpy as np +import pytest from pydantic.tools import parse_obj_as, schema_json_of from docarray.base_document.io.json import orjson_dumps from docarray.typing import AnyEmbedding +@pytest.mark.proto def test_proto_embedding(): embedding = parse_obj_as(AnyEmbedding, np.zeros((3, 224, 224))) diff --git a/tests/units/typing/tensor/test_tensor.py b/tests/units/typing/tensor/test_tensor.py index c7b72d77303..1d36a4c355e 100644 --- a/tests/units/typing/tensor/test_tensor.py +++ b/tests/units/typing/tensor/test_tensor.py @@ -8,6 +8,7 @@ from docarray.typing.tensor import NdArrayEmbedding +@pytest.mark.proto def test_proto_tensor(): tensor = parse_obj_as(NdArray, np.zeros((3, 224, 224))) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index 0e75484d7c7..019089c54bf 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -1,12 +1,35 @@ import numpy as np import pytest -import tensorflow as tf +from google.protobuf import __version__ as __pb__version__ from pydantic import schema_json_of from pydantic.tools import parse_obj_as -from tensorflow.python.framework.errors_impl import InvalidArgumentError from docarray.base_document.io.json import orjson_dumps -from docarray.typing import TensorFlowTensor + +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp # type: ignore + from tensorflow.python.framework.errors_impl import InvalidArgumentError + + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass + + +@pytest.mark.proto +@pytest.mark.skipif( + __pb__version__.startswith('4'), reason="Tensorflow requires protobuf 3" +) +def test_proto_tensor(): + from docarray.proto.pb2.docarray_pb2 import NdArrayProto + + tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) + proto = tensor.to_protobuf() + assert isinstance(proto, NdArrayProto) + + from_proto = TensorFlowTensor.from_protobuf(proto) + assert isinstance(from_proto, TensorFlowTensor) + assert tnp.allclose(tensor.tensor, from_proto.tensor) def test_json_schema(): diff --git a/tests/units/typing/tensor/test_torch_tensor.py b/tests/units/typing/tensor/test_torch_tensor.py index b2b836a5a05..e56adef11ca 100644 --- a/tests/units/typing/tensor/test_torch_tensor.py +++ b/tests/units/typing/tensor/test_torch_tensor.py @@ -6,6 +6,7 @@ from docarray.typing import TorchEmbedding, TorchTensor +@pytest.mark.proto def test_proto_tensor(): tensor = parse_obj_as(TorchTensor, torch.zeros(3, 224, 224)) diff --git a/tests/units/typing/url/test_image_url.py b/tests/units/typing/url/test_image_url.py index 63ade56c3a4..cc95a074c3c 100644 --- a/tests/units/typing/url/test_image_url.py +++ b/tests/units/typing/url/test_image_url.py @@ -32,6 +32,7 @@ def test_image_url(): assert isinstance(tensor, np.ndarray) +@pytest.mark.proto def test_proto_image_url(): uri = parse_obj_as(ImageUrl, REMOTE_JPG) diff --git a/tests/units/typing/url/test_mesh_url.py b/tests/units/typing/url/test_mesh_url.py index 534a052929a..83297cde56d 100644 --- a/tests/units/typing/url/test_mesh_url.py +++ b/tests/units/typing/url/test_mesh_url.py @@ -85,6 +85,7 @@ def test_validation(file_format, path_to_file): assert isinstance(url, str) +@pytest.mark.proto def test_proto_mesh_url(): uri = parse_obj_as(Mesh3DUrl, REMOTE_OBJ_FILE) uri._to_node_protobuf() diff --git a/tests/units/typing/url/test_point_cloud_url.py b/tests/units/typing/url/test_point_cloud_url.py index 5d36686901a..f209a62afb9 100644 --- a/tests/units/typing/url/test_point_cloud_url.py +++ b/tests/units/typing/url/test_point_cloud_url.py @@ -88,6 +88,7 @@ def test_validation(file_format, path_to_file): assert isinstance(url, str) +@pytest.mark.proto def test_proto_point_cloud_url(): uri = parse_obj_as(PointCloud3DUrl, REMOTE_OBJ_FILE) uri._to_node_protobuf() From 68bdd779a87d9d881e1ea6abfc2a549432afe4f2 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:25:04 +0100 Subject: [PATCH 27/70] test: introduce pytest tensorflow marker Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 37 ++++++++++++++++--- pyproject.toml | 3 +- tests/integrations/typing/test_tensor.py | 19 ++++++++-- .../typing/test_tensorflow_tensor.py | 13 +++++-- .../integrations/typing/test_typing_proto.py | 5 ++- 5 files changed, 63 insertions(+), 14 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 3823d7e473f..86b5f639a54 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -58,8 +58,8 @@ jobs: run: | python -m pip install --upgrade pip python -m pip install poetry - pip install tensorflow==2.11.0 poetry install --without dev + pip install tensorflow==2.11.0 - name: Test basic import run: poetry run python -c 'from docarray import DocumentArray, BaseDocument' @@ -117,7 +117,7 @@ jobs: - name: Test id: test run: | - poetry run pytest ${{ matrix.test-path }} + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} timeout-minutes: 30 # env: # JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" @@ -161,11 +161,11 @@ jobs: - name: Test id: test run: | - poetry run pytest ${{ matrix.test-path }} + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} timeout-minutes: 30 - docarray-test-proto3: +`docarray-test-proto3: needs: [lint-ruff, check-black, import-test] runs-on: ubuntu-latest strategy: @@ -184,7 +184,6 @@ jobs: python -m pip install poetry poetry install --all-extras pip install protobuf==3.19.0 # we check that we support 3.19 - pip install tensorflow==2.11.0 - name: Test id: test @@ -193,6 +192,34 @@ jobs: timeout-minutes: 30 + docarray-test-tensorflow: + needs: [lint-ruff, check-black, import-test] + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: [3.7] + steps: + - uses: actions/checkout@v2.5.0 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Prepare environment + run: | + python -m pip install --upgrade pip + python -m pip install poetry + poetry install --all-extras + pip install protobuf==3.19.0 # we check that we support 3.19 + pip install tensorflow==2.11.0 + + - name: Test + id: test + run: | + poetry run pytest -k 'tensorflow' tests + timeout-minutes: 30 + + # just for blocking the merge until all parallel core-test are successful success-all-test: needs: [docarray-test, check-mypy] diff --git a/pyproject.toml b/pyproject.toml index f41df6db23a..2c2c2a48abe 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -81,5 +81,6 @@ markers = [ "slow: marks tests as slow (deselect with '-m \"not slow\"')", "internet: marks tests as requiring internet (deselect with '-m \"not internet\"')", "asyncio: marks that run async tests", - "proto: mark tests that run with proto" + "proto: mark tests that run with proto", + "tensorflow: marks test using tensorflow and proto 3" ] diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index 2c0cff23ee8..04fd44a9874 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -1,10 +1,17 @@ import numpy as np -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp # type: ignore +import pytest import torch from docarray import BaseDocument -from docarray.typing import AnyTensor, NdArray, TensorFlowTensor, TorchTensor +from docarray.typing import AnyTensor, NdArray, TorchTensor + +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp # type: ignore + + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass def test_set_tensor(): @@ -23,6 +30,12 @@ class MyDocument(BaseDocument): assert isinstance(d.tensor, torch.Tensor) assert (d.tensor == torch.zeros((3, 224, 224))).all() + +@pytest.mark.tensorflow +def test_set_tensor(): + class MyDocument(BaseDocument): + tensor: AnyTensor + d = MyDocument(tensor=tf.zeros((3, 224, 224))) assert isinstance(d.tensor, TensorFlowTensor) diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index bb403de1173..c82e9f63394 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -1,10 +1,17 @@ -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp # type: ignore +import pytest from docarray import BaseDocument -from docarray.typing import TensorFlowTensor +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp # type: ignore + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass + + +@pytest.mark.tensorflow def test_set_tensorflow_tensor(): class MyDocument(BaseDocument): t: TensorFlowTensor diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index dd4b2ef9dc2..9d5b8040ee3 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -11,7 +11,6 @@ Mesh3DUrl, NdArray, PointCloud3DUrl, - TensorFlowTensor, TextUrl, TorchTensor, ) @@ -50,10 +49,12 @@ class Mymmdoc(BaseDocument): assert isinstance(value, doc._get_field_type(field)) -@pytest.mark.proto +@pytest.mark.tensorflow def test_proto_all_types_proto3(): import tensorflow as tf + from docarray.typing import TensorFlowTensor + class Mymmdoc(BaseDocument): tensor: NdArray torch_tensor: TorchTensor From fcd5b744ea94eb3dee31caefd25905c79f18e69b Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:32:44 +0100 Subject: [PATCH 28/70] fix: typo in ci.yml Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 86b5f639a54..b3e747bf3aa 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -165,7 +165,7 @@ jobs: timeout-minutes: 30 -`docarray-test-proto3: + docarray-test-proto3: needs: [lint-ruff, check-black, import-test] runs-on: ubuntu-latest strategy: From 1e8e240813f6ce410abe98f91e30d90e5400bf54 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:46:13 +0100 Subject: [PATCH 29/70] fix: try tf import Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index ffba747dbbd..c60c3e8e465 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -35,7 +35,7 @@ from docarray.typing import NdArray, TensorFlowTensor except (ImportError, TypeError): - pass + TensorFlowTensor = None T = TypeVar('T', bound='DocumentArrayStacked') From a5988ab5954619b60e300cb0452f79bc87fb07af Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:49:08 +0100 Subject: [PATCH 30/70] fix: mypy Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index c60c3e8e465..f87cf6f9727 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -35,7 +35,7 @@ from docarray.typing import NdArray, TensorFlowTensor except (ImportError, TypeError): - TensorFlowTensor = None + TensorFlowTensor = None # type: ignore T = TypeVar('T', bound='DocumentArrayStacked') From 156a5088113f2e6149f980c929b59be8c965f422 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:51:01 +0100 Subject: [PATCH 31/70] fix: ndarray import Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index f87cf6f9727..d48b992b763 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -15,6 +15,7 @@ from docarray.array.abstract_array import AnyDocumentArray from docarray.array.array import DocumentArray from docarray.base_document import AnyDocument, BaseDocument +from docarray.typing import NdArray from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union @@ -33,7 +34,7 @@ try: import tensorflow as tf # type: ignore - from docarray.typing import NdArray, TensorFlowTensor + from docarray.typing import TensorFlowTensor except (ImportError, TypeError): TensorFlowTensor = None # type: ignore From a29f5c1b5874bc5d19000278622e01935c90bd33 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 13:56:26 +0100 Subject: [PATCH 32/70] fix: tf import Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index d48b992b763..62c46957095 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -35,8 +35,11 @@ import tensorflow as tf # type: ignore from docarray.typing import TensorFlowTensor + + tf_available = True except (ImportError, TypeError): TensorFlowTensor = None # type: ignore + tf_available = False T = TypeVar('T', bound='DocumentArrayStacked') @@ -146,7 +149,7 @@ def _create_columns( columns: Dict[str, Union[DocumentArrayStacked, AbstractTensor]] = dict() for field, type_ in column_schema.items(): - if isinstance(getattr(docs[0], field), TensorFlowTensor): + if tf_available and isinstance(getattr(docs[0], field), TensorFlowTensor): tf_stack = [] for i, doc in enumerate(docs): val = getattr(doc, field) From eb6a53ab4b74d3065413115173773e62669bde88 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 14:15:04 +0100 Subject: [PATCH 33/70] test: add tf markers Signed-off-by: anna-charlotte --- tests/integrations/typing/test_tensor.py | 2 +- tests/units/array/test_array_stacked_tf.py | 47 ++++++++++++++----- .../tensorflow_backend/test_basics.py | 21 +++++++-- .../tensorflow_backend/test_metrics.py | 15 ++++-- .../tensorflow_backend/test_retrieval.py | 14 ++++-- .../typing/tensor/test_tensor_flow_tensor.py | 17 +++++-- 6 files changed, 88 insertions(+), 28 deletions(-) diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index 04fd44a9874..afd0095bd87 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -11,7 +11,7 @@ from docarray.typing import TensorFlowTensor except (ImportError, TypeError): - pass + TensorFlowTensor = None def test_set_tensor(): diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index ffe70a00f50..ac56953f32e 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -1,14 +1,21 @@ from typing import Optional, Union import pytest -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp from docarray import BaseDocument, DocumentArray from docarray.array import DocumentArrayStacked -from docarray.typing import AnyTensor, NdArray, TensorFlowTensor +from docarray.typing import AnyTensor, NdArray + +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass +@pytest.mark.tensorflow @pytest.fixture() def batch(): class Image(BaseDocument): @@ -23,20 +30,24 @@ class Image(BaseDocument): return batch.stack() +@pytest.mark.tensorflow def test_len(batch): assert len(batch) == 10 +@pytest.mark.tensorflow def test_getitem(batch): for i in range(len(batch)): assert tnp.allclose(batch[i].tensor.tensor, tf.zeros((3, 224, 224))) +@pytest.mark.tensorflow def test_iterator(batch): for doc in batch: assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) +@pytest.mark.tensorflow def test_stack_setter(batch): batch.tensor = tf.ones((10, 3, 224, 224)) @@ -44,6 +55,7 @@ def test_stack_setter(batch): assert tnp.allclose(batch.tensor, tf.ones((10, 3, 224, 224))) +@pytest.mark.tensorflow def test_set_after_stacking(batch): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -58,12 +70,14 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, batch.tensor.tensor[i]) +@pytest.mark.tensorflow def test_stack_optional(batch): assert tnp.allclose(batch._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224))) assert tnp.allclose(batch.tensor.tensor, tf.zeros((10, 3, 224, 224))) +@pytest.mark.tensorflow def test_stack_mod_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -84,6 +98,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(batch.img.tensor.tensor, tf.zeros((10, 3, 224, 224))) +@pytest.mark.tensorflow def test_convert_to_da(batch): da = batch.unstack() @@ -91,6 +106,7 @@ def test_convert_to_da(batch): assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) +@pytest.mark.tensorflow def test_unstack_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -109,6 +125,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(doc.img.tensor.tensor, tf.zeros((3, 224, 224))) +@pytest.mark.tensorflow def test_stack_call(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -124,6 +141,7 @@ class Image(BaseDocument): assert da.tensor.tensor.shape == (10, 3, 224, 224) +@pytest.mark.tensorflow def test_context_manager(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -146,6 +164,7 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, tf.ones((3, 224, 224))) +@pytest.mark.tensorflow def test_stack_union(): class Image(BaseDocument): tensor: Union[NdArray[3, 224, 224], TensorFlowTensor[3, 224, 224]] @@ -160,26 +179,26 @@ class Image(BaseDocument): batch.stack() -@pytest.mark.parametrize( - 'tensor_type,tensor', - [(TensorFlowTensor, tf.zeros((3, 224, 224)))], -) -def test_any_tensor_with_tf(tensor_type, tensor): +@pytest.mark.tensorflow +def test_any_tensor_with_tf(): + tensor = tf.zeros((3, 224, 224)) + class Image(BaseDocument): tensor: AnyTensor da = DocumentArray[Image]( [Image(tensor=tensor) for _ in range(10)], - tensor_type=tensor_type, + tensor_type=TensorFlowTensor, ).stack() for i in range(len(da)): assert tnp.allclose(da[i].tensor.tensor, tensor) assert 'tensor' in da._columns.keys() - assert isinstance(da._columns['tensor'], tensor_type) + assert isinstance(da._columns['tensor'], TensorFlowTensor) +@pytest.mark.tensorflow def test_any_tensor_with_optional(): tensor = tf.zeros((3, 224, 224)) @@ -202,6 +221,7 @@ class TopDoc(BaseDocument): assert isinstance(da.img._columns['tensor'].tensor, tf.Tensor) +@pytest.mark.tensorflow def test_get_from_slice_stacked(): class Doc(BaseDocument): text: str @@ -218,18 +238,19 @@ class Doc(BaseDocument): assert tensors.shape == (5, 3, 224, 224) -@pytest.mark.parametrize('tensor_backend', [TensorFlowTensor]) -def test_stack_none(tensor_backend): +@pytest.mark.tensorflow +def test_stack_none(): class MyDoc(BaseDocument): tensor: Optional[AnyTensor] da = DocumentArray[MyDoc]( - [MyDoc(tensor=None) for _ in range(10)], tensor_type=tensor_backend + [MyDoc(tensor=None) for _ in range(10)], tensor_type=TensorFlowTensor ).stack() assert 'tensor' in da._columns.keys() +@pytest.mark.tensorflow def test_keep_dtype_tf(): class MyDoc(BaseDocument): tensor: TensorFlowTensor diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 286042e6bc6..05629308ae3 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -1,11 +1,16 @@ import numpy as np import pytest -import tensorflow as tf -from docarray.computation.tensorflow_backend import TensorFlowCompBackend -from docarray.typing import TensorFlowTensor +try: + import tensorflow as tf + from docarray.computation.tensorflow_backend import TensorFlowCompBackend + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass + +@pytest.mark.tensorflow @pytest.mark.parametrize( 'array,result', [ @@ -20,6 +25,7 @@ def test_n_dim(array, result): assert TensorFlowCompBackend.n_dim(array) == result +@pytest.mark.tensorflow @pytest.mark.parametrize( 'array,result', [ @@ -35,41 +41,48 @@ def test_shape(array, result): assert type(shape) == tuple +@pytest.mark.tensorflow def test_to_device(): array = TensorFlowTensor(tf.constant([1, 2, 3])) array = TensorFlowCompBackend.to_device(array, 'CPU:0') assert array.tensor.device.endswith('CPU:0') +@pytest.mark.tensorflow @pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) def test_dtype(dtype): array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=dtype)) assert TensorFlowCompBackend.dtype(array) == dtype +@pytest.mark.tensorflow def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) assert array.tensor.shape == (10, 3) +@pytest.mark.tensorflow def test_empty_dtype(): tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) assert tf_tensor.tensor.shape == (10, 3) assert tf_tensor.tensor.dtype == tf.int32 +@pytest.mark.tensorflow def test_empty_device(): tensor = TensorFlowCompBackend.empty((10, 3), device='CPU:0') assert tensor.tensor.shape == (10, 3) assert tensor.tensor.device.endswith('CPU:0') +@pytest.mark.tensorflow def test_squeeze(): tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) squeezed = TensorFlowCompBackend.squeeze(tensor) assert squeezed.tensor.shape == (3,) +@pytest.mark.tensorflow @pytest.mark.parametrize( 'array,t_range,x_range,result', [ @@ -101,12 +114,14 @@ def test_minmax_normalize(array, t_range, x_range, result): assert np.allclose(output.tensor, result) +@pytest.mark.tensorflow def test_reshape(): tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) assert reshaped.tensor.shape == (224, 224, 3) +@pytest.mark.tensorflow def test_stack(): t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) t1 = TensorFlowTensor(tf.ones((3, 224, 224))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index f7e193872c7..2997d51e7a8 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -1,11 +1,18 @@ -import tensorflow as tf +import pytest + +try: + import tensorflow as tf + + from docarray.computation.tensorflow_backend import TensorFlowCompBackend + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass -from docarray.computation.tensorflow_backend import TensorFlowCompBackend -from docarray.typing import TensorFlowTensor metrics = TensorFlowCompBackend.Metrics +@pytest.mark.tensorflow def test_cosine_sim_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -21,6 +28,7 @@ def test_cosine_sim_tf(): tf.experimental.numpy.allclose(diag_dists, tf.ones(5)) +@pytest.mark.tensorflow def test_euclidean_dist_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -53,6 +61,7 @@ def test_euclidean_dist_tf(): ) +@pytest.mark.tensorflow def test_sqeuclidean_dist_torch(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 9ec9c6aad0d..1961af28549 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -1,10 +1,17 @@ -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp +import pytest from docarray.computation.tensorflow_backend import TensorFlowCompBackend -from docarray.typing import TensorFlowTensor +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass + + +@pytest.mark.tensorflow def test_top_k_descending_false(): top_k = TensorFlowCompBackend.Retrieval.top_k @@ -31,6 +38,7 @@ def test_top_k_descending_false(): assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) +@pytest.mark.tensorflow def test_top_k_descending_true(): top_k = TensorFlowCompBackend.Retrieval.top_k diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index 019089c54bf..28d1e94cb5c 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -1,6 +1,5 @@ import numpy as np import pytest -from google.protobuf import __version__ as __pb__version__ from pydantic import schema_json_of from pydantic.tools import parse_obj_as @@ -16,10 +15,7 @@ pass -@pytest.mark.proto -@pytest.mark.skipif( - __pb__version__.startswith('4'), reason="Tensorflow requires protobuf 3" -) +@pytest.mark.tensorflow def test_proto_tensor(): from docarray.proto.pb2.docarray_pb2 import NdArrayProto @@ -32,15 +28,18 @@ def test_proto_tensor(): assert tnp.allclose(tensor.tensor, from_proto.tensor) +@pytest.mark.tensorflow def test_json_schema(): schema_json_of(TensorFlowTensor) +@pytest.mark.tensorflow def test_dump_json(): tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) orjson_dumps(tensor) +@pytest.mark.tensorflow def test_unwrap(): tf_tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) unwrapped = tf_tensor.unwrap() @@ -52,6 +51,7 @@ def test_unwrap(): assert np.allclose(unwrapped, np.zeros((3, 224, 224))) +@pytest.mark.tensorflow def test_from_ndarray(): nd = np.array([1, 2, 3]) tensor = TensorFlowTensor.from_ndarray(nd) @@ -59,6 +59,7 @@ def test_from_ndarray(): assert isinstance(tensor.tensor, tf.Tensor) +@pytest.mark.tensorflow def test_parametrized(): # correct shape, single axis tf_tensor = parse_obj_as(TensorFlowTensor[128], tf.zeros(128)) @@ -83,6 +84,7 @@ def test_parametrized(): parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 224))) +@pytest.mark.tensorflow def test_parametrized_with_str(): # test independent variable dimensions tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((3, 224, 224))) @@ -114,6 +116,7 @@ def test_parametrized_with_str(): _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60))) +@pytest.mark.tensorflow @pytest.mark.parametrize('shape', [(3, 224, 224), (224, 224, 3)]) def test_parameterized_tensor_class_name(shape): MyTFT = TensorFlowTensor[3, 224, 224] @@ -127,6 +130,7 @@ def test_parameterized_tensor_class_name(shape): assert f'{tensor.tensor[0][0][0]}' == '0.0' +@pytest.mark.tensorflow def test_parametrized_subclass(): c1 = TensorFlowTensor[128] c2 = TensorFlowTensor[128] @@ -136,6 +140,7 @@ def test_parametrized_subclass(): assert not issubclass(c1, TensorFlowTensor[256]) +@pytest.mark.tensorflow def test_parametrized_instance(): t = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert isinstance(t, TensorFlowTensor[128]) @@ -147,12 +152,14 @@ def test_parametrized_instance(): assert not isinstance(t, TensorFlowTensor[2, 2, 64]) +@pytest.mark.tensorflow def test_parametrized_equality(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert tf.experimental.numpy.allclose(t1.tensor, t2.tensor) +@pytest.mark.tensorflow def test_parametrized_operations(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) From a2afa419bcb783d3162ed87c487acec5bdae2fd8 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 14:29:02 +0100 Subject: [PATCH 34/70] test: fix unit tests Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 2 +- tests/units/array/test_array.py | 8 +++- .../units/typing/tensor/test_cross_backend.py | 9 ++++- tests/units/util/test_typing.py | 39 +++++++++++++++---- 4 files changed, 48 insertions(+), 10 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index b3e747bf3aa..f9c6e3106f7 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -210,7 +210,7 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --all-extras - pip install protobuf==3.19.0 # we check that we support 3.19 + pip install protobuf==3.19.0 pip install tensorflow==2.11.0 - name: Test diff --git a/tests/units/array/test_array.py b/tests/units/array/test_array.py index 09efd08470d..0e0f47f9a4b 100644 --- a/tests/units/array/test_array.py +++ b/tests/units/array/test_array.py @@ -5,7 +5,12 @@ import torch from docarray import BaseDocument, DocumentArray -from docarray.typing import NdArray, TensorFlowTensor, TorchTensor +from docarray.typing import NdArray, TorchTensor + +try: + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass @pytest.fixture() @@ -208,6 +213,7 @@ class Mmdoc(BaseDocument): assert text == f'hello{i}' +@pytest.mark.tensorflow def test_get_bulk_attributes_union_type_nested(): class MyDoc(BaseDocument): embedding: Union[Optional[TorchTensor], Optional[NdArray]] diff --git a/tests/units/typing/tensor/test_cross_backend.py b/tests/units/typing/tensor/test_cross_backend.py index baefeb91683..702cd678d6f 100644 --- a/tests/units/typing/tensor/test_cross_backend.py +++ b/tests/units/typing/tensor/test_cross_backend.py @@ -1,9 +1,16 @@ import numpy as np +import pytest from pydantic import parse_obj_as -from docarray.typing import NdArray, TensorFlowTensor, TorchTensor +from docarray.typing import NdArray, TorchTensor +try: + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass + +@pytest.mark.tensorflow def test_coercion_behavior(): t_np = parse_obj_as(NdArray[128], np.zeros(128)) t_th = parse_obj_as(TorchTensor[128], np.zeros(128)) diff --git a/tests/units/util/test_typing.py b/tests/units/util/test_typing.py index aa21c1071d0..66eb135d7ff 100644 --- a/tests/units/util/test_typing.py +++ b/tests/units/util/test_typing.py @@ -2,20 +2,23 @@ import pytest -from docarray.typing import NdArray, TensorFlowTensor, TorchTensor +from docarray.typing import NdArray, TorchTensor from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union, is_type_tensor +try: + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + TensorFlowTensor = None + @pytest.mark.parametrize( 'type_, is_tensor', [ (int, False), - (TensorFlowTensor, True), (TorchTensor, True), (NdArray, True), (AbstractTensor, True), - (Optional[TensorFlowTensor], False), (Optional[TorchTensor], False), (Union[TorchTensor, NdArray], False), (None, False), @@ -26,23 +29,45 @@ def test_is_type_tensor(type_, is_tensor): assert is_type_tensor(type_) == is_tensor +@pytest.mark.tensorflow +@pytest.mark.parametrize( + 'type_, is_tensor', + [ + (TensorFlowTensor, True), + (Optional[TensorFlowTensor], False), + ], +) +def test_is_type_tensor_with_tf(type_, is_tensor): + assert is_type_tensor(type_) == is_tensor + + @pytest.mark.parametrize( 'type_, is_union_tensor', [ (int, False), - (TensorFlowTensor, False), (TorchTensor, False), (NdArray, False), - (Optional[TensorFlowTensor], True), (Optional[TorchTensor], True), (Optional[NdArray], True), (Union[NdArray, TorchTensor], True), - (Union[NdArray, TorchTensor, TensorFlowTensor], True), (Union[NdArray, TorchTensor, AbstractTensor], True), (Union[NdArray, TorchTensor, Optional[TorchTensor]], True), - (Union[NdArray, TorchTensor, Optional[TensorFlowTensor]], True), (Union[NdArray, TorchTensor, None], True), ], ) def test_is_union_type_tensor(type_, is_union_tensor): assert is_tensor_union(type_) == is_union_tensor + + +@pytest.mark.tensorflow +@pytest.mark.parametrize( + 'type_, is_union_tensor', + [ + (TensorFlowTensor, False), + (Optional[TensorFlowTensor], True), + (Union[NdArray, TorchTensor, TensorFlowTensor], True), + (Union[NdArray, TorchTensor, Optional[TensorFlowTensor]], True), + ], +) +def test_is_union_type_tensor_with_tf(type_, is_union_tensor): + assert is_tensor_union(type_) == is_union_tensor From 9cc04ddd1d96825d8f2a4e5a1fb12dd740e84a44 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 14:46:11 +0100 Subject: [PATCH 35/70] test: fix unit tests Signed-off-by: anna-charlotte --- .../tensorflow_backend/test_basics.py | 50 +++++++++---------- .../tensorflow_backend/test_metrics.py | 7 ++- .../tensorflow_backend/test_retrieval.py | 3 +- 3 files changed, 29 insertions(+), 31 deletions(-) diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 05629308ae3..7c896749647 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -12,30 +12,30 @@ @pytest.mark.tensorflow @pytest.mark.parametrize( - 'array,result', + 'shape,result', [ - (tf.zeros((5)), 1), - (tf.zeros((1, 5)), 2), - (tf.zeros((5, 5)), 2), - (tf.zeros(()), 0), + ((5), 1), + ((1, 5), 2), + ((5, 5), 2), + ((), 0), ], ) -def test_n_dim(array, result): - array = TensorFlowTensor(array) +def test_n_dim(shape, result): + array = TensorFlowTensor(tf.zeros(shape)) assert TensorFlowCompBackend.n_dim(array) == result @pytest.mark.tensorflow @pytest.mark.parametrize( - 'array,result', + 'shape,result', [ - (tf.zeros((10,)), (10,)), - (tf.zeros((5, 5)), (5, 5)), - (tf.zeros(()), ()), + ((10,), (10,)), + ((5, 5), (5, 5)), + ((), ()), ], ) -def test_shape(array, result): - array = TensorFlowTensor(array) +def test_shape(shape, result): + array = TensorFlowTensor(tf.zeros(shape)) shape = TensorFlowCompBackend.shape(array) assert shape == result assert type(shape) == tuple @@ -49,9 +49,9 @@ def test_to_device(): @pytest.mark.tensorflow -@pytest.mark.parametrize('dtype', [tf.int64, tf.float64, tf.int8, tf.double]) +@pytest.mark.parametrize('dtype', ['int64', 'float64', 'int8', 'double']) def test_dtype(dtype): - array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=dtype)) + array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=getattr(tf, dtype))) assert TensorFlowCompBackend.dtype(array) == dtype @@ -84,34 +84,34 @@ def test_squeeze(): @pytest.mark.tensorflow @pytest.mark.parametrize( - 'array,t_range,x_range,result', + 'data_input,t_range,x_range,data_result', [ ( - tf.constant([0, 1, 2, 3, 4, 5]), + [0, 1, 2, 3, 4, 5], (0, 10), None, - tf.constant([0, 2, 4, 6, 8, 10]), + [0, 2, 4, 6, 8, 10], ), ( - tf.constant([0, 1, 2, 3, 4, 5]), + [0, 1, 2, 3, 4, 5], (0, 10), (0, 10), - tf.constant([0, 1, 2, 3, 4, 5]), + [0, 1, 2, 3, 4, 5], ), ( - tf.constant([[0.0, 1.0], [0.0, 1.0]]), + [[0.0, 1.0], [0.0, 1.0]], (0, 10), None, - tf.constant([[0.0, 10.0], [0.0, 10.0]]), + [[0.0, 10.0], [0.0, 10.0]], ), ], ) -def test_minmax_normalize(array, t_range, x_range, result): - array = TensorFlowTensor(array) +def test_minmax_normalize(data_input, t_range, x_range, data_result): + array = TensorFlowTensor(tf.constant(data_input)) output = TensorFlowCompBackend.minmax_normalize( tensor=array, t_range=t_range, x_range=x_range ) - assert np.allclose(output.tensor, result) + assert np.allclose(output.tensor, tf.constant(data_result)) @pytest.mark.tensorflow diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index 2997d51e7a8..354b61612e5 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -5,11 +5,10 @@ from docarray.computation.tensorflow_backend import TensorFlowCompBackend from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass - -metrics = TensorFlowCompBackend.Metrics + metrics = TensorFlowCompBackend.Metrics +except (ImportError, TypeError): + metrics = None @pytest.mark.tensorflow diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 1961af28549..0eb789b9e1d 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -1,11 +1,10 @@ import pytest -from docarray.computation.tensorflow_backend import TensorFlowCompBackend - try: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp + from docarray.computation.tensorflow_backend import TensorFlowCompBackend from docarray.typing import TensorFlowTensor except (ImportError, TypeError): pass From bfffc2d06c5e04dcc6f0103ac0cf92e96282f377 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 14:55:08 +0100 Subject: [PATCH 36/70] fix: tf in array stacked Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index 62c46957095..eeffb99160d 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -228,7 +228,7 @@ def __getitem__(self, item): # note this should handle slices # NOTE: this could be speed up by using a cache for field in self._columns.keys(): value = self._columns[field] - if isinstance(value, TensorFlowTensor): + if tf_available and isinstance(value, TensorFlowTensor): new_value = value.tensor[item] else: new_value = value[item] @@ -243,7 +243,7 @@ def _get_slice(self: T, item: slice) -> T: """ columns_sliced: Dict[str, AnyTensor] = {} for k, col in self._columns.items(): - if isinstance(col, TensorFlowTensor): + if tf_available and isinstance(col, TensorFlowTensor): columns_sliced[k] = TensorFlowTensor(col.tensor[item]) else: columns_sliced[k] = col[item] @@ -303,7 +303,7 @@ def unstack(self: T) -> DocumentArray: for i, doc in enumerate(self._docs): for field in self._columns.keys(): val = self._columns[field] - if isinstance(val, TensorFlowTensor): + if tf_available and isinstance(val, TensorFlowTensor): setattr(doc, field, val.tensor[i]) else: setattr(doc, field, val[i]) From 6e715b35b1d0adec167fc26319d38d83b8a2f7f4 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:04:41 +0100 Subject: [PATCH 37/70] test: tf Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index ac56953f32e..de11d1ef5ad 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -11,8 +11,9 @@ import tensorflow._api.v2.experimental.numpy as tnp from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass +except (ImportError, TypeError) as e: + print(f"e = {e}") + TensorFlow = None @pytest.mark.tensorflow From cc2e83701d3e0379515b6109d9594b02aec96941 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:10:25 +0100 Subject: [PATCH 38/70] chore: pytest proto marker call with -m Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index f9c6e3106f7..883bafffe99 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -188,7 +188,7 @@ jobs: - name: Test id: test run: | - poetry run pytest -k 'proto' tests + poetry run pytest -m 'proto' tests timeout-minutes: 30 @@ -216,7 +216,7 @@ jobs: - name: Test id: test run: | - poetry run pytest -k 'tensorflow' tests + poetry run pytest -m 'tensorflow' tests timeout-minutes: 30 From 125f66cf6fe101b50478323f6a23544ca11ebae6 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:33:45 +0100 Subject: [PATCH 39/70] fix: instance check use instance shape Signed-off-by: anna-charlotte --- docarray/typing/tensor/abstract_tensor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docarray/typing/tensor/abstract_tensor.py b/docarray/typing/tensor/abstract_tensor.py index 5ae2d0e7b6b..cde591cbcd6 100644 --- a/docarray/typing/tensor/abstract_tensor.py +++ b/docarray/typing/tensor/abstract_tensor.py @@ -69,7 +69,7 @@ def __instancecheck__(cls, instance): _cls.__unparametrizedcls__ ): # This is not None if the tensor is parametrized if ( - _cls.get_comp_backend().shape(instance) + instance.get_comp_backend().shape(instance) != _cls.__docarray_target_shape__ ): return False From d6506d1456968a7b03e995d8eeb42262579673ae Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:34:30 +0100 Subject: [PATCH 40/70] fix: tf tests Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index de11d1ef5ad..7b5e24a7b5a 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -13,10 +13,9 @@ from docarray.typing import TensorFlowTensor except (ImportError, TypeError) as e: print(f"e = {e}") - TensorFlow = None + TensorFlowTensor = None -@pytest.mark.tensorflow @pytest.fixture() def batch(): class Image(BaseDocument): From 73f8b0ac70b683c579c2f3750fef6bfed73c0de9 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:41:49 +0100 Subject: [PATCH 41/70] fix: test Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 7b5e24a7b5a..9b4361800ba 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -12,7 +12,7 @@ from docarray.typing import TensorFlowTensor except (ImportError, TypeError) as e: - print(f"e = {e}") + print(f"exception = {e}") TensorFlowTensor = None From 2d9162cd3f72c7e3e2217f34e0578470bfa0b181 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 15:49:15 +0100 Subject: [PATCH 42/70] fix: add print statement to debug Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 9b4361800ba..665d9e302ac 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -11,6 +11,8 @@ import tensorflow._api.v2.experimental.numpy as tnp from docarray.typing import TensorFlowTensor + + print("passed!") except (ImportError, TypeError) as e: print(f"exception = {e}") TensorFlowTensor = None From ef335adb6dfba22ed5160499005add8656377b28 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 16:09:14 +0100 Subject: [PATCH 43/70] fix: tf test Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 15 +++------------ 1 file changed, 3 insertions(+), 12 deletions(-) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 665d9e302ac..0ddbd266dc8 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -1,21 +1,12 @@ from typing import Optional, Union import pytest +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp from docarray import BaseDocument, DocumentArray from docarray.array import DocumentArrayStacked -from docarray.typing import AnyTensor, NdArray - -try: - import tensorflow as tf - import tensorflow._api.v2.experimental.numpy as tnp - - from docarray.typing import TensorFlowTensor - - print("passed!") -except (ImportError, TypeError) as e: - print(f"exception = {e}") - TensorFlowTensor = None +from docarray.typing import AnyTensor, NdArray, TensorFlowTensor @pytest.fixture() From 1e85f7a47d215236a3feb446dc7c9487227fd4be Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 16:19:40 +0100 Subject: [PATCH 44/70] test: only tf Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 194 +++++++++++++++++++-------------------- 1 file changed, 97 insertions(+), 97 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 883bafffe99..7e2cbd34bd5 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -91,105 +91,105 @@ jobs: # echo "matrix=$value" >> $GITHUB_OUTPUT # outputs: # matrix: ${{ steps.set-matrix.outputs.matrix }} - - docarray-test: - needs: [lint-ruff, check-black, import-test] - runs-on: ubuntu-latest - strategy: - fail-fast: false - matrix: - python-version: [3.7] -# test-path: ${{fromJson(needs.prep-testbed.outputs.matrix)}} - test-path: [tests/integrations, tests/units] - steps: - - uses: actions/checkout@v2.5.0 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - - name: Prepare environment - run: | - python -m pip install --upgrade pip - python -m pip install poetry - poetry install --all-extras - pip install tensorflow==2.11.0 - - - name: Test - id: test - run: | - poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} - timeout-minutes: 30 -# env: -# JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" -# - name: Check codecov file -# id: check_files -# uses: andstor/file-existence-action@v1 +# +# docarray-test: +# needs: [lint-ruff, check-black, import-test] +# runs-on: ubuntu-latest +# strategy: +# fail-fast: false +# matrix: +# python-version: [3.7] +## test-path: ${{fromJson(needs.prep-testbed.outputs.matrix)}} +# test-path: [tests/integrations, tests/units] +# steps: +# - uses: actions/checkout@v2.5.0 +# - name: Set up Python ${{ matrix.python-version }} +# uses: actions/setup-python@v4 # with: -# files: "coverage.xml" -# - name: Upload coverage from test to Codecov -# uses: codecov/codecov-action@v3.1.1 -# if: steps.check_files.outputs.files_exists == 'true' && ${{ matrix.python-version }} == '3.7' +# python-version: ${{ matrix.python-version }} +# - name: Prepare environment +# run: | +# python -m pip install --upgrade pip +# python -m pip install poetry +# poetry install --all-extras +# pip install tensorflow==2.11.0 +# +# - name: Test +# id: test +# run: | +# poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} +# timeout-minutes: 30 +## env: +## JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" +## - name: Check codecov file +## id: check_files +## uses: andstor/file-existence-action@v1 +## with: +## files: "coverage.xml" +## - name: Upload coverage from test to Codecov +## uses: codecov/codecov-action@v3.1.1 +## if: steps.check_files.outputs.files_exists == 'true' && ${{ matrix.python-version }} == '3.7' +## with: +## file: coverage.xml +## flags: ${{ steps.test.outputs.codecov_flag }} +## fail_ci_if_error: false +## token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos +# +# +# +# docarray-test-uncaped: # do test without using poetry lock. This does not block ci passing +# needs: [lint-ruff, check-black, import-test] +# runs-on: ubuntu-latest +# strategy: +# fail-fast: false +# matrix: +# python-version: [3.7] +# test-path: [tests/integrations, tests/units] +# steps: +# - uses: actions/checkout@v2.5.0 +# - name: Set up Python ${{ matrix.python-version }} +# uses: actions/setup-python@v4 # with: -# file: coverage.xml -# flags: ${{ steps.test.outputs.codecov_flag }} -# fail_ci_if_error: false -# token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos - - - - docarray-test-uncaped: # do test without using poetry lock. This does not block ci passing - needs: [lint-ruff, check-black, import-test] - runs-on: ubuntu-latest - strategy: - fail-fast: false - matrix: - python-version: [3.7] - test-path: [tests/integrations, tests/units] - steps: - - uses: actions/checkout@v2.5.0 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - - name: Prepare environment - run: | - python -m pip install --upgrade pip - python -m pip install poetry - rm poetry.lock - poetry install --all-extras - - - name: Test - id: test - run: | - poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} - timeout-minutes: 30 - - - docarray-test-proto3: - needs: [lint-ruff, check-black, import-test] - runs-on: ubuntu-latest - strategy: - fail-fast: false - matrix: - python-version: [3.7] - steps: - - uses: actions/checkout@v2.5.0 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - - name: Prepare environment - run: | - python -m pip install --upgrade pip - python -m pip install poetry - poetry install --all-extras - pip install protobuf==3.19.0 # we check that we support 3.19 - - - name: Test - id: test - run: | - poetry run pytest -m 'proto' tests - timeout-minutes: 30 +# python-version: ${{ matrix.python-version }} +# - name: Prepare environment +# run: | +# python -m pip install --upgrade pip +# python -m pip install poetry +# rm poetry.lock +# poetry install --all-extras +# +# - name: Test +# id: test +# run: | +# poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} +# timeout-minutes: 30 +# +# +# docarray-test-proto3: +# needs: [lint-ruff, check-black, import-test] +# runs-on: ubuntu-latest +# strategy: +# fail-fast: false +# matrix: +# python-version: [3.7] +# steps: +# - uses: actions/checkout@v2.5.0 +# - name: Set up Python ${{ matrix.python-version }} +# uses: actions/setup-python@v4 +# with: +# python-version: ${{ matrix.python-version }} +# - name: Prepare environment +# run: | +# python -m pip install --upgrade pip +# python -m pip install poetry +# poetry install --all-extras +# pip install protobuf==3.19.0 # we check that we support 3.19 +# +# - name: Test +# id: test +# run: | +# poetry run pytest -m 'proto' tests +# timeout-minutes: 30 docarray-test-tensorflow: From ca8d1d1124fcfdbcaf4b5ac65d17d8a57565ea13 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 16:23:35 +0100 Subject: [PATCH 45/70] test: remove tests for debugging Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 7e2cbd34bd5..642cd3d8886 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -219,17 +219,17 @@ jobs: poetry run pytest -m 'tensorflow' tests timeout-minutes: 30 - - # just for blocking the merge until all parallel core-test are successful - success-all-test: - needs: [docarray-test, check-mypy] - if: always() - runs-on: ubuntu-latest - steps: - - uses: technote-space/workflow-conclusion-action@v2 - - name: Check Failure - if: env.WORKFLOW_CONCLUSION == 'failure' - run: exit 1 - - name: Success - if: ${{ success() }} - run: echo "All Done" +# +# # just for blocking the merge until all parallel core-test are successful +# success-all-test: +# needs: [docarray-test, check-mypy] +# if: always() +# runs-on: ubuntu-latest +# steps: +# - uses: technote-space/workflow-conclusion-action@v2 +# - name: Check Failure +# if: env.WORKFLOW_CONCLUSION == 'failure' +# run: exit 1 +# - name: Success +# if: ${{ success() }} +# run: echo "All Done" From 1dd9c6e2b7abe154eb5aa6ae80ce284815cb54ee Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 16:30:10 +0100 Subject: [PATCH 46/70] test: add all tests back to ci yml Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 225 ++++++++++++++++++++------------------- 1 file changed, 113 insertions(+), 112 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 642cd3d8886..7c816aefd03 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -54,7 +54,7 @@ jobs: uses: actions/setup-python@v4 with: python-version: 3.7 - - name: Prepare enviroment + - name: Prepare environment run: | python -m pip install --upgrade pip python -m pip install poetry @@ -91,105 +91,105 @@ jobs: # echo "matrix=$value" >> $GITHUB_OUTPUT # outputs: # matrix: ${{ steps.set-matrix.outputs.matrix }} -# -# docarray-test: -# needs: [lint-ruff, check-black, import-test] -# runs-on: ubuntu-latest -# strategy: -# fail-fast: false -# matrix: -# python-version: [3.7] -## test-path: ${{fromJson(needs.prep-testbed.outputs.matrix)}} -# test-path: [tests/integrations, tests/units] -# steps: -# - uses: actions/checkout@v2.5.0 -# - name: Set up Python ${{ matrix.python-version }} -# uses: actions/setup-python@v4 -# with: -# python-version: ${{ matrix.python-version }} -# - name: Prepare environment -# run: | -# python -m pip install --upgrade pip -# python -m pip install poetry -# poetry install --all-extras -# pip install tensorflow==2.11.0 -# -# - name: Test -# id: test -# run: | -# poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} -# timeout-minutes: 30 -## env: -## JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" -## - name: Check codecov file -## id: check_files -## uses: andstor/file-existence-action@v1 -## with: -## files: "coverage.xml" -## - name: Upload coverage from test to Codecov -## uses: codecov/codecov-action@v3.1.1 -## if: steps.check_files.outputs.files_exists == 'true' && ${{ matrix.python-version }} == '3.7' -## with: -## file: coverage.xml -## flags: ${{ steps.test.outputs.codecov_flag }} -## fail_ci_if_error: false -## token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos -# -# -# -# docarray-test-uncaped: # do test without using poetry lock. This does not block ci passing -# needs: [lint-ruff, check-black, import-test] -# runs-on: ubuntu-latest -# strategy: -# fail-fast: false -# matrix: -# python-version: [3.7] -# test-path: [tests/integrations, tests/units] -# steps: -# - uses: actions/checkout@v2.5.0 -# - name: Set up Python ${{ matrix.python-version }} -# uses: actions/setup-python@v4 + + docarray-test: + needs: [lint-ruff, check-black, import-test] + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: [3.7] +# test-path: ${{fromJson(needs.prep-testbed.outputs.matrix)}} + test-path: [tests/integrations, tests/units] + steps: + - uses: actions/checkout@v2.5.0 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Prepare environment + run: | + python -m pip install --upgrade pip + python -m pip install poetry + poetry install --all-extras + pip install tensorflow==2.11.0 + + - name: Test + id: test + run: | + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} + timeout-minutes: 30 +# env: +# JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" +# - name: Check codecov file +# id: check_files +# uses: andstor/file-existence-action@v1 # with: -# python-version: ${{ matrix.python-version }} -# - name: Prepare environment -# run: | -# python -m pip install --upgrade pip -# python -m pip install poetry -# rm poetry.lock -# poetry install --all-extras -# -# - name: Test -# id: test -# run: | -# poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} -# timeout-minutes: 30 -# -# -# docarray-test-proto3: -# needs: [lint-ruff, check-black, import-test] -# runs-on: ubuntu-latest -# strategy: -# fail-fast: false -# matrix: -# python-version: [3.7] -# steps: -# - uses: actions/checkout@v2.5.0 -# - name: Set up Python ${{ matrix.python-version }} -# uses: actions/setup-python@v4 +# files: "coverage.xml" +# - name: Upload coverage from test to Codecov +# uses: codecov/codecov-action@v3.1.1 +# if: steps.check_files.outputs.files_exists == 'true' && ${{ matrix.python-version }} == '3.7' # with: -# python-version: ${{ matrix.python-version }} -# - name: Prepare environment -# run: | -# python -m pip install --upgrade pip -# python -m pip install poetry -# poetry install --all-extras -# pip install protobuf==3.19.0 # we check that we support 3.19 -# -# - name: Test -# id: test -# run: | -# poetry run pytest -m 'proto' tests -# timeout-minutes: 30 +# file: coverage.xml +# flags: ${{ steps.test.outputs.codecov_flag }} +# fail_ci_if_error: false +# token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos + + + + docarray-test-uncaped: # do test without using poetry lock. This does not block ci passing + needs: [lint-ruff, check-black, import-test] + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: [3.7] + test-path: [tests/integrations, tests/units] + steps: + - uses: actions/checkout@v2.5.0 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Prepare environment + run: | + python -m pip install --upgrade pip + python -m pip install poetry + rm poetry.lock + poetry install --all-extras + + - name: Test + id: test + run: | + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} + timeout-minutes: 30 + + + docarray-test-proto3: + needs: [lint-ruff, check-black, import-test] + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: [3.7] + steps: + - uses: actions/checkout@v2.5.0 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Prepare environment + run: | + python -m pip install --upgrade pip + python -m pip install poetry + poetry install --all-extras + pip install protobuf==3.19.0 # we check that we support 3.19 + + - name: Test + id: test + run: | + poetry run pytest -m 'proto' tests + timeout-minutes: 30 docarray-test-tensorflow: @@ -216,20 +216,21 @@ jobs: - name: Test id: test run: | + pip show tensorflow poetry run pytest -m 'tensorflow' tests timeout-minutes: 30 -# -# # just for blocking the merge until all parallel core-test are successful -# success-all-test: -# needs: [docarray-test, check-mypy] -# if: always() -# runs-on: ubuntu-latest -# steps: -# - uses: technote-space/workflow-conclusion-action@v2 -# - name: Check Failure -# if: env.WORKFLOW_CONCLUSION == 'failure' -# run: exit 1 -# - name: Success -# if: ${{ success() }} -# run: echo "All Done" + + # just for blocking the merge until all parallel core-test are successful + success-all-test: + needs: [docarray-test, check-mypy] + if: always() + runs-on: ubuntu-latest + steps: + - uses: technote-space/workflow-conclusion-action@v2 + - name: Check Failure + if: env.WORKFLOW_CONCLUSION == 'failure' + run: exit 1 + - name: Success + if: ${{ success() }} + run: echo "All Done" From f8d8426e8b981fed4202faa7287104a8fb56d6e4 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 16:37:50 +0100 Subject: [PATCH 47/70] test: fix import Signed-off-by: anna-charlotte --- tests/integrations/typing/test_tensorflow_tensor.py | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index c82e9f63394..a7ce9ace800 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -1,14 +1,9 @@ import pytest +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray import BaseDocument - -try: - import tensorflow as tf - import tensorflow._api.v2.experimental.numpy as tnp # type: ignore - - from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass +from docarray.typing import TensorFlowTensor @pytest.mark.tensorflow From 269cf0f231a281e545471081f171ae29f0c90083 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:04:24 +0100 Subject: [PATCH 48/70] test: ci debugging Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 2 +- tests/units/array/test_array_stacked_tf.py | 17 +++++++++++------ 2 files changed, 12 insertions(+), 7 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 7c816aefd03..93c5904c26b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -198,7 +198,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.7] + python-version: [3.8] steps: - uses: actions/checkout@v2.5.0 - name: Set up Python ${{ matrix.python-version }} diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 0ddbd266dc8..a5accf0b6d8 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -1,12 +1,17 @@ +import sys from typing import Optional, Union -import pytest -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp +print(f"getattr(sys, 'base_prefix', None) = {getattr(sys, 'base_prefix', None)}") +print(f"getattr(sys, 'real_prefix', None) = {getattr(sys, 'real_prefix', None)}") +print(f"sys.prefix = {sys.prefix}") -from docarray import BaseDocument, DocumentArray -from docarray.array import DocumentArrayStacked -from docarray.typing import AnyTensor, NdArray, TensorFlowTensor +import pytest # noqa: E402 +import tensorflow as tf # noqa: E402 +import tensorflow._api.v2.experimental.numpy as tnp # noqa: E402 + +from docarray import BaseDocument, DocumentArray # noqa: E402 +from docarray.array import DocumentArrayStacked # noqa: E402 +from docarray.typing import AnyTensor, NdArray, TensorFlowTensor # noqa: E402 @pytest.fixture() From 9bcb81619a66c9e87aba06375afbe482c13ae7a6 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:09:43 +0100 Subject: [PATCH 49/70] test: change pytest marker for tf Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 6 ++-- pyproject.toml | 2 +- tests/integrations/typing/test_tensor.py | 2 +- .../typing/test_tensorflow_tensor.py | 2 +- .../integrations/typing/test_typing_proto.py | 2 +- tests/units/array/test_array.py | 2 +- tests/units/array/test_array_stacked_tf.py | 34 +++++++++---------- .../tensorflow_backend/test_basics.py | 22 ++++++------ .../tensorflow_backend/test_metrics.py | 6 ++-- .../tensorflow_backend/test_retrieval.py | 4 +-- .../units/typing/tensor/test_cross_backend.py | 2 +- .../typing/tensor/test_tensor_flow_tensor.py | 24 ++++++------- tests/units/util/test_typing.py | 4 +-- 13 files changed, 56 insertions(+), 56 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 93c5904c26b..4b1c0a7a303 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -117,7 +117,7 @@ jobs: - name: Test id: test run: | - poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} + poetry run pytest -m "not tensor_flow" ${{ matrix.test-path }} timeout-minutes: 30 # env: # JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" @@ -161,7 +161,7 @@ jobs: - name: Test id: test run: | - poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} + poetry run pytest -m "not tensor_flow" ${{ matrix.test-path }} timeout-minutes: 30 @@ -217,7 +217,7 @@ jobs: id: test run: | pip show tensorflow - poetry run pytest -m 'tensorflow' tests + poetry run pytest -m 'tensor_flow' tests timeout-minutes: 30 diff --git a/pyproject.toml b/pyproject.toml index 2c2c2a48abe..bf1ce4420bf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -82,5 +82,5 @@ markers = [ "internet: marks tests as requiring internet (deselect with '-m \"not internet\"')", "asyncio: marks that run async tests", "proto: mark tests that run with proto", - "tensorflow: marks test using tensorflow and proto 3" + "tensor_flow: marks test using tensorflow and proto 3" ] diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index afd0095bd87..086a4009a15 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -31,7 +31,7 @@ class MyDocument(BaseDocument): assert (d.tensor == torch.zeros((3, 224, 224))).all() -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_set_tensor(): class MyDocument(BaseDocument): tensor: AnyTensor diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index a7ce9ace800..2982c87ae8a 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -6,7 +6,7 @@ from docarray.typing import TensorFlowTensor -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_set_tensorflow_tensor(): class MyDocument(BaseDocument): t: TensorFlowTensor diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index 9d5b8040ee3..c819a6ee57d 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -49,7 +49,7 @@ class Mymmdoc(BaseDocument): assert isinstance(value, doc._get_field_type(field)) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_proto_all_types_proto3(): import tensorflow as tf diff --git a/tests/units/array/test_array.py b/tests/units/array/test_array.py index 0e0f47f9a4b..ccc141cd3e1 100644 --- a/tests/units/array/test_array.py +++ b/tests/units/array/test_array.py @@ -213,7 +213,7 @@ class Mmdoc(BaseDocument): assert text == f'hello{i}' -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_get_bulk_attributes_union_type_nested(): class MyDoc(BaseDocument): embedding: Union[Optional[TorchTensor], Optional[NdArray]] diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index a5accf0b6d8..cb56d450871 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -28,24 +28,24 @@ class Image(BaseDocument): return batch.stack() -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_len(batch): assert len(batch) == 10 -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_getitem(batch): for i in range(len(batch)): assert tnp.allclose(batch[i].tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_iterator(batch): for doc in batch: assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_setter(batch): batch.tensor = tf.ones((10, 3, 224, 224)) @@ -53,7 +53,7 @@ def test_stack_setter(batch): assert tnp.allclose(batch.tensor, tf.ones((10, 3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_set_after_stacking(batch): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -68,14 +68,14 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, batch.tensor.tensor[i]) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_optional(batch): assert tnp.allclose(batch._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224))) assert tnp.allclose(batch.tensor.tensor, tf.zeros((10, 3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_mod_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -96,7 +96,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(batch.img.tensor.tensor, tf.zeros((10, 3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_convert_to_da(batch): da = batch.unstack() @@ -104,7 +104,7 @@ def test_convert_to_da(batch): assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_unstack_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -123,7 +123,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(doc.img.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_call(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -139,7 +139,7 @@ class Image(BaseDocument): assert da.tensor.tensor.shape == (10, 3, 224, 224) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_context_manager(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -162,7 +162,7 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, tf.ones((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_union(): class Image(BaseDocument): tensor: Union[NdArray[3, 224, 224], TensorFlowTensor[3, 224, 224]] @@ -177,7 +177,7 @@ class Image(BaseDocument): batch.stack() -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_any_tensor_with_tf(): tensor = tf.zeros((3, 224, 224)) @@ -196,7 +196,7 @@ class Image(BaseDocument): assert isinstance(da._columns['tensor'], TensorFlowTensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_any_tensor_with_optional(): tensor = tf.zeros((3, 224, 224)) @@ -219,7 +219,7 @@ class TopDoc(BaseDocument): assert isinstance(da.img._columns['tensor'].tensor, tf.Tensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_get_from_slice_stacked(): class Doc(BaseDocument): text: str @@ -236,7 +236,7 @@ class Doc(BaseDocument): assert tensors.shape == (5, 3, 224, 224) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack_none(): class MyDoc(BaseDocument): tensor: Optional[AnyTensor] @@ -248,7 +248,7 @@ class MyDoc(BaseDocument): assert 'tensor' in da._columns.keys() -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_keep_dtype_tf(): class MyDoc(BaseDocument): tensor: TensorFlowTensor diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 7c896749647..02fd8c784c6 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize( 'shape,result', [ @@ -25,7 +25,7 @@ def test_n_dim(shape, result): assert TensorFlowCompBackend.n_dim(array) == result -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize( 'shape,result', [ @@ -41,48 +41,48 @@ def test_shape(shape, result): assert type(shape) == tuple -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_to_device(): array = TensorFlowTensor(tf.constant([1, 2, 3])) array = TensorFlowCompBackend.to_device(array, 'CPU:0') assert array.tensor.device.endswith('CPU:0') -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize('dtype', ['int64', 'float64', 'int8', 'double']) def test_dtype(dtype): array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=getattr(tf, dtype))) assert TensorFlowCompBackend.dtype(array) == dtype -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) assert array.tensor.shape == (10, 3) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_empty_dtype(): tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) assert tf_tensor.tensor.shape == (10, 3) assert tf_tensor.tensor.dtype == tf.int32 -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_empty_device(): tensor = TensorFlowCompBackend.empty((10, 3), device='CPU:0') assert tensor.tensor.shape == (10, 3) assert tensor.tensor.device.endswith('CPU:0') -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_squeeze(): tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) squeezed = TensorFlowCompBackend.squeeze(tensor) assert squeezed.tensor.shape == (3,) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize( 'data_input,t_range,x_range,data_result', [ @@ -114,14 +114,14 @@ def test_minmax_normalize(data_input, t_range, x_range, data_result): assert np.allclose(output.tensor, tf.constant(data_result)) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_reshape(): tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) assert reshaped.tensor.shape == (224, 224, 3) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_stack(): t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) t1 = TensorFlowTensor(tf.ones((3, 224, 224))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index 354b61612e5..86d80ba7c51 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -11,7 +11,7 @@ metrics = None -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_cosine_sim_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -27,7 +27,7 @@ def test_cosine_sim_tf(): tf.experimental.numpy.allclose(diag_dists, tf.ones(5)) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_euclidean_dist_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -60,7 +60,7 @@ def test_euclidean_dist_tf(): ) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_sqeuclidean_dist_torch(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 0eb789b9e1d..6f6629629a1 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_top_k_descending_false(): top_k = TensorFlowCompBackend.Retrieval.top_k @@ -37,7 +37,7 @@ def test_top_k_descending_false(): assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_top_k_descending_true(): top_k = TensorFlowCompBackend.Retrieval.top_k diff --git a/tests/units/typing/tensor/test_cross_backend.py b/tests/units/typing/tensor/test_cross_backend.py index 702cd678d6f..190dac3007d 100644 --- a/tests/units/typing/tensor/test_cross_backend.py +++ b/tests/units/typing/tensor/test_cross_backend.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_coercion_behavior(): t_np = parse_obj_as(NdArray[128], np.zeros(128)) t_th = parse_obj_as(TorchTensor[128], np.zeros(128)) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index 28d1e94cb5c..93f2dff4bd2 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -15,7 +15,7 @@ pass -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_proto_tensor(): from docarray.proto.pb2.docarray_pb2 import NdArrayProto @@ -28,18 +28,18 @@ def test_proto_tensor(): assert tnp.allclose(tensor.tensor, from_proto.tensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_json_schema(): schema_json_of(TensorFlowTensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_dump_json(): tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) orjson_dumps(tensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_unwrap(): tf_tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) unwrapped = tf_tensor.unwrap() @@ -51,7 +51,7 @@ def test_unwrap(): assert np.allclose(unwrapped, np.zeros((3, 224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_from_ndarray(): nd = np.array([1, 2, 3]) tensor = TensorFlowTensor.from_ndarray(nd) @@ -59,7 +59,7 @@ def test_from_ndarray(): assert isinstance(tensor.tensor, tf.Tensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized(): # correct shape, single axis tf_tensor = parse_obj_as(TensorFlowTensor[128], tf.zeros(128)) @@ -84,7 +84,7 @@ def test_parametrized(): parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 224))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized_with_str(): # test independent variable dimensions tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((3, 224, 224))) @@ -116,7 +116,7 @@ def test_parametrized_with_str(): _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60))) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize('shape', [(3, 224, 224), (224, 224, 3)]) def test_parameterized_tensor_class_name(shape): MyTFT = TensorFlowTensor[3, 224, 224] @@ -130,7 +130,7 @@ def test_parameterized_tensor_class_name(shape): assert f'{tensor.tensor[0][0][0]}' == '0.0' -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized_subclass(): c1 = TensorFlowTensor[128] c2 = TensorFlowTensor[128] @@ -140,7 +140,7 @@ def test_parametrized_subclass(): assert not issubclass(c1, TensorFlowTensor[256]) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized_instance(): t = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert isinstance(t, TensorFlowTensor[128]) @@ -152,14 +152,14 @@ def test_parametrized_instance(): assert not isinstance(t, TensorFlowTensor[2, 2, 64]) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized_equality(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert tf.experimental.numpy.allclose(t1.tensor, t2.tensor) -@pytest.mark.tensorflow +@pytest.mark.tensor_flow def test_parametrized_operations(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) diff --git a/tests/units/util/test_typing.py b/tests/units/util/test_typing.py index 66eb135d7ff..e2bf1ad9ab2 100644 --- a/tests/units/util/test_typing.py +++ b/tests/units/util/test_typing.py @@ -29,7 +29,7 @@ def test_is_type_tensor(type_, is_tensor): assert is_type_tensor(type_) == is_tensor -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize( 'type_, is_tensor', [ @@ -59,7 +59,7 @@ def test_is_union_type_tensor(type_, is_union_tensor): assert is_tensor_union(type_) == is_union_tensor -@pytest.mark.tensorflow +@pytest.mark.tensor_flow @pytest.mark.parametrize( 'type_, is_union_tensor', [ From dac79e2761913c70e038064f77f3a7530a8c4dec Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:13:22 +0100 Subject: [PATCH 50/70] test: change python version back Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4b1c0a7a303..9b2fed040e1 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -198,7 +198,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.8] + python-version: [3.7] steps: - uses: actions/checkout@v2.5.0 - name: Set up Python ${{ matrix.python-version }} From 8046e9917ce0980c900aa68864abc003257cf2a9 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:13:56 +0100 Subject: [PATCH 51/70] test: revert Signed-off-by: anna-charlotte --- tests/units/array/test_array_stacked_tf.py | 17 ++++++----------- 1 file changed, 6 insertions(+), 11 deletions(-) diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index cb56d450871..654c7d7412b 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -1,17 +1,12 @@ -import sys from typing import Optional, Union -print(f"getattr(sys, 'base_prefix', None) = {getattr(sys, 'base_prefix', None)}") -print(f"getattr(sys, 'real_prefix', None) = {getattr(sys, 'real_prefix', None)}") -print(f"sys.prefix = {sys.prefix}") +import pytest +import tensorflow as tf +import tensorflow._api.v2.experimental.numpy as tnp -import pytest # noqa: E402 -import tensorflow as tf # noqa: E402 -import tensorflow._api.v2.experimental.numpy as tnp # noqa: E402 - -from docarray import BaseDocument, DocumentArray # noqa: E402 -from docarray.array import DocumentArrayStacked # noqa: E402 -from docarray.typing import AnyTensor, NdArray, TensorFlowTensor # noqa: E402 +from docarray import BaseDocument, DocumentArray +from docarray.array import DocumentArrayStacked +from docarray.typing import AnyTensor, NdArray, TensorFlowTensor @pytest.fixture() From e325244670d45e366316ab1fe2bd7e12d4317ca2 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:19:46 +0100 Subject: [PATCH 52/70] test: debugging Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 9b2fed040e1..41565066955 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -210,8 +210,8 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --all-extras - pip install protobuf==3.19.0 - pip install tensorflow==2.11.0 + poetry run pip install protobuf==3.19.0 + poetry run pip install tensorflow==2.11.0 - name: Test id: test From b7db1c83558696ec4b3f42f1d30920fffa8ab753 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:26:47 +0100 Subject: [PATCH 53/70] fix: test Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 41565066955..2788db3fcf7 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -216,7 +216,7 @@ jobs: - name: Test id: test run: | - pip show tensorflow + poetry run pip show tensorflow poetry run pytest -m 'tensor_flow' tests timeout-minutes: 30 From 9d1ef56d01c528f317b535607dc3a5ca8bdd9370 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:41:26 +0100 Subject: [PATCH 54/70] fix: tests Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 12 +++---- pyproject.toml | 2 +- tests/integrations/typing/test_tensor.py | 2 +- .../typing/test_tensorflow_tensor.py | 2 +- .../integrations/typing/test_typing_proto.py | 2 +- tests/units/array/test_array.py | 2 +- tests/units/array/test_array_stacked_tf.py | 34 +++++++++---------- .../tensorflow_backend/test_basics.py | 22 ++++++------ .../tensorflow_backend/test_metrics.py | 6 ++-- .../tensorflow_backend/test_retrieval.py | 4 +-- .../units/typing/tensor/test_cross_backend.py | 2 +- .../typing/tensor/test_tensor_flow_tensor.py | 24 ++++++------- tests/units/util/test_typing.py | 4 +-- 13 files changed, 59 insertions(+), 59 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 2788db3fcf7..4c97dae8361 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -59,7 +59,7 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --without dev - pip install tensorflow==2.11.0 + poetry run pip install tensorflow==2.11.0 - name: Test basic import run: poetry run python -c 'from docarray import DocumentArray, BaseDocument' @@ -112,12 +112,12 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --all-extras - pip install tensorflow==2.11.0 + poetry run pip install tensorflow==2.11.0 - name: Test id: test run: | - poetry run pytest -m "not tensor_flow" ${{ matrix.test-path }} + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} timeout-minutes: 30 # env: # JINA_AUTH_TOKEN: "${{ secrets.JINA_AUTH_TOKEN }}" @@ -161,7 +161,7 @@ jobs: - name: Test id: test run: | - poetry run pytest -m "not tensor_flow" ${{ matrix.test-path }} + poetry run pytest -m "not tensorflow" ${{ matrix.test-path }} timeout-minutes: 30 @@ -183,7 +183,7 @@ jobs: python -m pip install --upgrade pip python -m pip install poetry poetry install --all-extras - pip install protobuf==3.19.0 # we check that we support 3.19 + poetry run pip install protobuf==3.19.0 # we check that we support 3.19 - name: Test id: test @@ -217,7 +217,7 @@ jobs: id: test run: | poetry run pip show tensorflow - poetry run pytest -m 'tensor_flow' tests + poetry run pytest -m 'tensorflow' tests timeout-minutes: 30 diff --git a/pyproject.toml b/pyproject.toml index bf1ce4420bf..2c2c2a48abe 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -82,5 +82,5 @@ markers = [ "internet: marks tests as requiring internet (deselect with '-m \"not internet\"')", "asyncio: marks that run async tests", "proto: mark tests that run with proto", - "tensor_flow: marks test using tensorflow and proto 3" + "tensorflow: marks test using tensorflow and proto 3" ] diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index 086a4009a15..afd0095bd87 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -31,7 +31,7 @@ class MyDocument(BaseDocument): assert (d.tensor == torch.zeros((3, 224, 224))).all() -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_set_tensor(): class MyDocument(BaseDocument): tensor: AnyTensor diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index 2982c87ae8a..a7ce9ace800 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -6,7 +6,7 @@ from docarray.typing import TensorFlowTensor -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_set_tensorflow_tensor(): class MyDocument(BaseDocument): t: TensorFlowTensor diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index c819a6ee57d..9d5b8040ee3 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -49,7 +49,7 @@ class Mymmdoc(BaseDocument): assert isinstance(value, doc._get_field_type(field)) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_proto_all_types_proto3(): import tensorflow as tf diff --git a/tests/units/array/test_array.py b/tests/units/array/test_array.py index ccc141cd3e1..0e0f47f9a4b 100644 --- a/tests/units/array/test_array.py +++ b/tests/units/array/test_array.py @@ -213,7 +213,7 @@ class Mmdoc(BaseDocument): assert text == f'hello{i}' -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_get_bulk_attributes_union_type_nested(): class MyDoc(BaseDocument): embedding: Union[Optional[TorchTensor], Optional[NdArray]] diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 654c7d7412b..0ddbd266dc8 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -23,24 +23,24 @@ class Image(BaseDocument): return batch.stack() -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_len(batch): assert len(batch) == 10 -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_getitem(batch): for i in range(len(batch)): assert tnp.allclose(batch[i].tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_iterator(batch): for doc in batch: assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_setter(batch): batch.tensor = tf.ones((10, 3, 224, 224)) @@ -48,7 +48,7 @@ def test_stack_setter(batch): assert tnp.allclose(batch.tensor, tf.ones((10, 3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_set_after_stacking(batch): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -63,14 +63,14 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, batch.tensor.tensor[i]) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_optional(batch): assert tnp.allclose(batch._columns['tensor'].tensor, tf.zeros((10, 3, 224, 224))) assert tnp.allclose(batch.tensor.tensor, tf.zeros((10, 3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_mod_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -91,7 +91,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(batch.img.tensor.tensor, tf.zeros((10, 3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_convert_to_da(batch): da = batch.unstack() @@ -99,7 +99,7 @@ def test_convert_to_da(batch): assert tnp.allclose(doc.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_unstack_nested_document(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -118,7 +118,7 @@ class MMdoc(BaseDocument): assert tnp.allclose(doc.img.tensor.tensor, tf.zeros((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_call(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -134,7 +134,7 @@ class Image(BaseDocument): assert da.tensor.tensor.shape == (10, 3, 224, 224) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_context_manager(): class Image(BaseDocument): tensor: TensorFlowTensor[3, 224, 224] @@ -157,7 +157,7 @@ class Image(BaseDocument): assert tnp.allclose(doc.tensor.tensor, tf.ones((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_union(): class Image(BaseDocument): tensor: Union[NdArray[3, 224, 224], TensorFlowTensor[3, 224, 224]] @@ -172,7 +172,7 @@ class Image(BaseDocument): batch.stack() -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_any_tensor_with_tf(): tensor = tf.zeros((3, 224, 224)) @@ -191,7 +191,7 @@ class Image(BaseDocument): assert isinstance(da._columns['tensor'], TensorFlowTensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_any_tensor_with_optional(): tensor = tf.zeros((3, 224, 224)) @@ -214,7 +214,7 @@ class TopDoc(BaseDocument): assert isinstance(da.img._columns['tensor'].tensor, tf.Tensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_get_from_slice_stacked(): class Doc(BaseDocument): text: str @@ -231,7 +231,7 @@ class Doc(BaseDocument): assert tensors.shape == (5, 3, 224, 224) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack_none(): class MyDoc(BaseDocument): tensor: Optional[AnyTensor] @@ -243,7 +243,7 @@ class MyDoc(BaseDocument): assert 'tensor' in da._columns.keys() -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_keep_dtype_tf(): class MyDoc(BaseDocument): tensor: TensorFlowTensor diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 02fd8c784c6..7c896749647 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize( 'shape,result', [ @@ -25,7 +25,7 @@ def test_n_dim(shape, result): assert TensorFlowCompBackend.n_dim(array) == result -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize( 'shape,result', [ @@ -41,48 +41,48 @@ def test_shape(shape, result): assert type(shape) == tuple -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_to_device(): array = TensorFlowTensor(tf.constant([1, 2, 3])) array = TensorFlowCompBackend.to_device(array, 'CPU:0') assert array.tensor.device.endswith('CPU:0') -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize('dtype', ['int64', 'float64', 'int8', 'double']) def test_dtype(dtype): array = TensorFlowTensor(tf.constant([1, 2, 3], dtype=getattr(tf, dtype))) assert TensorFlowCompBackend.dtype(array) == dtype -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_empty(): array = TensorFlowCompBackend.empty((10, 3)) assert array.tensor.shape == (10, 3) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_empty_dtype(): tf_tensor = TensorFlowCompBackend.empty((10, 3), dtype=tf.int32) assert tf_tensor.tensor.shape == (10, 3) assert tf_tensor.tensor.dtype == tf.int32 -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_empty_device(): tensor = TensorFlowCompBackend.empty((10, 3), device='CPU:0') assert tensor.tensor.shape == (10, 3) assert tensor.tensor.device.endswith('CPU:0') -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_squeeze(): tensor = TensorFlowTensor(tf.zeros(shape=(1, 1, 3, 1))) squeezed = TensorFlowCompBackend.squeeze(tensor) assert squeezed.tensor.shape == (3,) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize( 'data_input,t_range,x_range,data_result', [ @@ -114,14 +114,14 @@ def test_minmax_normalize(data_input, t_range, x_range, data_result): assert np.allclose(output.tensor, tf.constant(data_result)) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_reshape(): tensor = TensorFlowTensor(tf.zeros((3, 224, 224))) reshaped = TensorFlowCompBackend.reshape(tensor, (224, 224, 3)) assert reshaped.tensor.shape == (224, 224, 3) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_stack(): t0 = TensorFlowTensor(tf.zeros((3, 224, 224))) t1 = TensorFlowTensor(tf.ones((3, 224, 224))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index 86d80ba7c51..354b61612e5 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -11,7 +11,7 @@ metrics = None -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_cosine_sim_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -27,7 +27,7 @@ def test_cosine_sim_tf(): tf.experimental.numpy.allclose(diag_dists, tf.ones(5)) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_euclidean_dist_tf(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) @@ -60,7 +60,7 @@ def test_euclidean_dist_tf(): ) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_sqeuclidean_dist_torch(): a = TensorFlowTensor(tf.random.normal((128,))) b = TensorFlowTensor(tf.random.normal((128,))) diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 6f6629629a1..0eb789b9e1d 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_top_k_descending_false(): top_k = TensorFlowCompBackend.Retrieval.top_k @@ -37,7 +37,7 @@ def test_top_k_descending_false(): assert tnp.allclose(indices.tensor[1], tf.constant([2, 4, 6])) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_top_k_descending_true(): top_k = TensorFlowCompBackend.Retrieval.top_k diff --git a/tests/units/typing/tensor/test_cross_backend.py b/tests/units/typing/tensor/test_cross_backend.py index 190dac3007d..702cd678d6f 100644 --- a/tests/units/typing/tensor/test_cross_backend.py +++ b/tests/units/typing/tensor/test_cross_backend.py @@ -10,7 +10,7 @@ pass -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_coercion_behavior(): t_np = parse_obj_as(NdArray[128], np.zeros(128)) t_th = parse_obj_as(TorchTensor[128], np.zeros(128)) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index 93f2dff4bd2..28d1e94cb5c 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -15,7 +15,7 @@ pass -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_proto_tensor(): from docarray.proto.pb2.docarray_pb2 import NdArrayProto @@ -28,18 +28,18 @@ def test_proto_tensor(): assert tnp.allclose(tensor.tensor, from_proto.tensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_json_schema(): schema_json_of(TensorFlowTensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_dump_json(): tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) orjson_dumps(tensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_unwrap(): tf_tensor = parse_obj_as(TensorFlowTensor, tf.zeros((3, 224, 224))) unwrapped = tf_tensor.unwrap() @@ -51,7 +51,7 @@ def test_unwrap(): assert np.allclose(unwrapped, np.zeros((3, 224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_from_ndarray(): nd = np.array([1, 2, 3]) tensor = TensorFlowTensor.from_ndarray(nd) @@ -59,7 +59,7 @@ def test_from_ndarray(): assert isinstance(tensor.tensor, tf.Tensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized(): # correct shape, single axis tf_tensor = parse_obj_as(TensorFlowTensor[128], tf.zeros(128)) @@ -84,7 +84,7 @@ def test_parametrized(): parse_obj_as(TensorFlowTensor[3, 224, 224], tf.zeros((224, 224))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized_with_str(): # test independent variable dimensions tf_tensor = parse_obj_as(TensorFlowTensor[3, 'x', 'y'], tf.zeros((3, 224, 224))) @@ -116,7 +116,7 @@ def test_parametrized_with_str(): _ = parse_obj_as(TensorFlowTensor[3, 'x', 'x'], tf.zeros((3, 60))) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize('shape', [(3, 224, 224), (224, 224, 3)]) def test_parameterized_tensor_class_name(shape): MyTFT = TensorFlowTensor[3, 224, 224] @@ -130,7 +130,7 @@ def test_parameterized_tensor_class_name(shape): assert f'{tensor.tensor[0][0][0]}' == '0.0' -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized_subclass(): c1 = TensorFlowTensor[128] c2 = TensorFlowTensor[128] @@ -140,7 +140,7 @@ def test_parametrized_subclass(): assert not issubclass(c1, TensorFlowTensor[256]) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized_instance(): t = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert isinstance(t, TensorFlowTensor[128]) @@ -152,14 +152,14 @@ def test_parametrized_instance(): assert not isinstance(t, TensorFlowTensor[2, 2, 64]) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized_equality(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) assert tf.experimental.numpy.allclose(t1.tensor, t2.tensor) -@pytest.mark.tensor_flow +@pytest.mark.tensorflow def test_parametrized_operations(): t1 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) t2 = parse_obj_as(TensorFlowTensor[128], tf.zeros((128,))) diff --git a/tests/units/util/test_typing.py b/tests/units/util/test_typing.py index e2bf1ad9ab2..66eb135d7ff 100644 --- a/tests/units/util/test_typing.py +++ b/tests/units/util/test_typing.py @@ -29,7 +29,7 @@ def test_is_type_tensor(type_, is_tensor): assert is_type_tensor(type_) == is_tensor -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize( 'type_, is_tensor', [ @@ -59,7 +59,7 @@ def test_is_union_type_tensor(type_, is_union_tensor): assert is_tensor_union(type_) == is_union_tensor -@pytest.mark.tensor_flow +@pytest.mark.tensorflow @pytest.mark.parametrize( 'type_, is_union_tensor', [ From 0467acaa2f6db35ebdc7f76c64a277fc612b0384 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 17:49:33 +0100 Subject: [PATCH 55/70] test: ignore paths Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4c97dae8361..e57dd5200f7 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -95,6 +95,9 @@ jobs: docarray-test: needs: [lint-ruff, check-black, import-test] runs-on: ubuntu-latest + paths-ignore: + - 'tests/units/array/test_array_stacked_tf.py' + - 'tests/integrations/typing/test_tensorflow_tensor.py' strategy: fail-fast: false matrix: From a25dcebfb93b6d45b30661bf59961a05012c8436 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 19:49:56 +0100 Subject: [PATCH 56/70] fix: tests Signed-off-by: anna-charlotte --- .github/workflows/ci.yml | 4 ---- tests/units/array/test_array_stacked_tf.py | 12 +++++++++--- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index e57dd5200f7..c07c5b5b90f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -95,9 +95,6 @@ jobs: docarray-test: needs: [lint-ruff, check-black, import-test] runs-on: ubuntu-latest - paths-ignore: - - 'tests/units/array/test_array_stacked_tf.py' - - 'tests/integrations/typing/test_tensorflow_tensor.py' strategy: fail-fast: false matrix: @@ -219,7 +216,6 @@ jobs: - name: Test id: test run: | - poetry run pip show tensorflow poetry run pytest -m 'tensorflow' tests timeout-minutes: 30 diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 0ddbd266dc8..514a376a7cd 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -1,12 +1,18 @@ from typing import Optional, Union import pytest -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp from docarray import BaseDocument, DocumentArray from docarray.array import DocumentArrayStacked -from docarray.typing import AnyTensor, NdArray, TensorFlowTensor +from docarray.typing import AnyTensor, NdArray + +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass @pytest.fixture() From 52064d26b957b2a943824f06dba72ae7d733ce58 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Mon, 6 Feb 2023 19:56:09 +0100 Subject: [PATCH 57/70] fix: tests Signed-off-by: anna-charlotte --- tests/integrations/typing/test_tensorflow_tensor.py | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index a7ce9ace800..c82e9f63394 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -1,9 +1,14 @@ import pytest -import tensorflow as tf -import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray import BaseDocument -from docarray.typing import TensorFlowTensor + +try: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp # type: ignore + + from docarray.typing import TensorFlowTensor +except (ImportError, TypeError): + pass @pytest.mark.tensorflow From 591cea1a2fedec7dedea21f5b23d05ef2d6edf3a Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 09:06:38 +0100 Subject: [PATCH 58/70] refactor: rename norm left and norm right Signed-off-by: anna-charlotte --- .../abstract_numpy_based_backend.py | 34 +++++++++-------- docarray/computation/numpy_backend.py | 4 +- docarray/computation/tensorflow_backend.py | 38 +++++++++---------- 3 files changed, 39 insertions(+), 37 deletions(-) diff --git a/docarray/computation/abstract_numpy_based_backend.py b/docarray/computation/abstract_numpy_based_backend.py index de9208516a6..85320b28938 100644 --- a/docarray/computation/abstract_numpy_based_backend.py +++ b/docarray/computation/abstract_numpy_based_backend.py @@ -18,32 +18,34 @@ class AbstractNumpyBasedBackend(AbstractComputationalBackend[T], ABC): """ _module: types.ModuleType - # _norm_left() and _norm_right() are functions to transform the input/output - # from cls_A -> cls_B and back depending on the subclass. This is especially - # important for the TensorFlowTensor class: - # If a TensorFlowTensor instance is input to a function, we first want to - # transform it to a tf.Tensor, since the tf.Tensor is what the _module of - # AbstractNumpyBasedBackend works on. Vice versa for the output. - _norm_left: Callable - _norm_right: Callable + # The method _get_tensor() transforms the input of the backends methods to a + # handleable type that the backends _module can work with, whereas _cast_output() + # casts the output of a methods back to the original input type. This is especially + # relevant w.r.t. the TensorFlowTensor class: + # If a TensorFlowTensor instance is input to a function, we first want to transform + # it to a tf.Tensor, since the tf.Tensor is what the TensorFlowBackend's _module + # (tnp) works on. If the function returns a tf.Tensor, we want to cast it back to a + # TensorFlowTensor. + _cast_output: Callable + _get_tensor: Callable @classmethod def stack(cls, tensors: Union[List[T], Tuple[T]], dim: int = 0) -> T: """Stack a list of tensors along a new axis.""" - norm_right = [cls._norm_right(t) for t in tensors] - return cls._norm_left(cls._module.stack(norm_right, axis=dim)) + t = [cls._get_tensor(t) for t in tensors] + return cls._cast_output(cls._module.stack(t, axis=dim)) @classmethod def n_dim(cls, array: T) -> int: """Get the number of the array dimensions.""" - return cls._module.ndim(cls._norm_right(array)) + return cls._module.ndim(cls._get_tensor(array)) @classmethod def squeeze(cls, tensor: T) -> T: """ Returns a tensor with all the dimensions of tensor of size 1 removed. """ - return cls._norm_left(cls._module.squeeze(cls._norm_right(tensor))) + return cls._cast_output(cls._module.squeeze(cls._get_tensor(tensor))) @classmethod def empty( @@ -54,12 +56,12 @@ def empty( ) -> T: if cls._module is np and device is not None: raise NotImplementedError('Numpy does not support devices (GPU).') - return cls._norm_left(cls._module.empty(shape, dtype=dtype)) + return cls._cast_output(cls._module.empty(shape, dtype=dtype)) @classmethod def shape(cls, array: T) -> Tuple[int, ...]: """Get shape of array""" - return tuple(cls._module.shape(cls._norm_right(array))) + return tuple(cls._module.shape(cls._get_tensor(array))) @classmethod def reshape(cls, array: T, shape: Tuple[int, ...]) -> T: @@ -71,9 +73,9 @@ def reshape(cls, array: T, shape: Tuple[int, ...]) -> T: :return: a array with the same data and number of elements as array but with the specified shape. """ - return cls._norm_left(cls._module.reshape(cls._norm_right(array), shape)) + return cls._cast_output(cls._module.reshape(cls._get_tensor(array), shape)) @classmethod def isnan(cls, tensor: T) -> T: """Check element-wise for nan and return result as a boolean array""" - return cls._norm_left(cls._module.isnan(cls._norm_right(tensor))) + return cls._cast_output(cls._module.isnan(cls._get_tensor(tensor))) diff --git a/docarray/computation/numpy_backend.py b/docarray/computation/numpy_backend.py index d50c1a1ce71..45b43d763d4 100644 --- a/docarray/computation/numpy_backend.py +++ b/docarray/computation/numpy_backend.py @@ -40,8 +40,8 @@ class NumpyCompBackend(AbstractNumpyBasedBackend): """ _module = np - _norm_left = identity - _norm_right = identity + _cast_output = identity + _get_tensor = identity @classmethod def to_device(cls, tensor: 'np.ndarray', device: str) -> 'np.ndarray': diff --git a/docarray/computation/tensorflow_backend.py b/docarray/computation/tensorflow_backend.py index 9903747f1b2..afee8668542 100644 --- a/docarray/computation/tensorflow_backend.py +++ b/docarray/computation/tensorflow_backend.py @@ -54,12 +54,12 @@ class TensorFlowCompBackend(AbstractNumpyBasedBackend[TensorFlowTensor]): """ _module = tnp - _norm_left: Callable = norm_left - _norm_right: Callable = norm_right + _cast_output: Callable = norm_left + _get_tensor: Callable = norm_right @classmethod def to_numpy(cls, array: 'TensorFlowTensor') -> 'np.ndarray': - return cls._norm_right(array).numpy() + return cls._get_tensor(array).numpy() @classmethod def none_value(cls) -> typing.Any: @@ -73,12 +73,12 @@ def to_device(cls, tensor: 'TensorFlowTensor', device: str) -> 'TensorFlowTensor return tensor else: with tf.device(device): - return cls._norm_left(tf.identity(cls._norm_right(tensor))) + return cls._cast_output(tf.identity(cls._get_tensor(tensor))) @classmethod def device(cls, tensor: 'TensorFlowTensor') -> Optional[str]: """Return device on which the tensor is allocated.""" - return cls._norm_right(tensor).device + return cls._get_tensor(tensor).device @classmethod def detach(cls, tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': @@ -88,12 +88,12 @@ def detach(cls, tensor: 'TensorFlowTensor') -> 'TensorFlowTensor': :param tensor: tensor to be detached :return: a detached tensor with the same data. """ - return cls._norm_left(tf.stop_gradient(cls._norm_right(tensor))) + return cls._cast_output(tf.stop_gradient(cls._get_tensor(tensor))) @classmethod def dtype(cls, tensor: 'TensorFlowTensor') -> tf.dtypes: """Get the data type of the tensor.""" - return cls._norm_right(tensor).dtype + return cls._get_tensor(tensor).dtype @classmethod def minmax_normalize( @@ -105,14 +105,14 @@ def minmax_normalize( ) -> 'TensorFlowTensor': a, b = t_range - t = tf.cast(cls._norm_right(tensor), tf.float32) + t = tf.cast(cls._get_tensor(tensor), tf.float32) min_d = x_range[0] if x_range else tnp.min(t, axis=-1, keepdims=True) max_d = x_range[1] if x_range else tnp.max(t, axis=-1, keepdims=True) i = (b - a) * (t - min_d) / (max_d - min_d + tf.constant(eps) + a) normalized = tnp.clip(i, *((a, b) if a < b else (b, a))) - return cls._norm_left(tf.cast(normalized, tensor.tensor.dtype)) + return cls._cast_output(tf.cast(normalized, tensor.tensor.dtype)) class Retrieval(AbstractComputationalBackend.Retrieval[TensorFlowTensor]): """ @@ -146,7 +146,7 @@ def top_k( if device is not None: values = comp_be.to_device(values, device) - tf_values: tf.Tensor = comp_be._norm_right(values) + tf_values: tf.Tensor = comp_be._get_tensor(values) if len(tf_values.shape) <= 1: tf_values = tf.expand_dims(tf_values, axis=0) @@ -165,7 +165,7 @@ def top_k( if not descending: res_values = -result.values - return comp_be._norm_left(res_values), comp_be._norm_left(res_indices) + return comp_be._cast_output(res_values), comp_be._cast_output(res_indices) class Metrics(AbstractComputationalBackend.Metrics[TensorFlowTensor]): """ @@ -194,8 +194,8 @@ def cosine_sim( x_mat[i_x] and y_mat[i_y]. """ comp_be = TensorFlowCompBackend - x_mat_tf: tf.Tensor = comp_be._norm_right(x_mat) - y_mat_tf: tf.Tensor = comp_be._norm_right(y_mat) + x_mat_tf: tf.Tensor = comp_be._get_tensor(x_mat) + y_mat_tf: tf.Tensor = comp_be._get_tensor(y_mat) with tf.device(device): x_mat_tf = tf.identity(x_mat_tf) @@ -214,7 +214,7 @@ def cosine_sim( sims = tf.squeeze(tf.linalg.matmul(a_norm, tf.transpose(b_norm))) sims = _unsqueeze_if_scalar(sims) - return comp_be._norm_left(sims) + return comp_be._cast_output(sims) @staticmethod def euclidean_dist( @@ -236,8 +236,8 @@ def euclidean_dist( x_mat[i_x] and y_mat[i_y]. """ comp_be = TensorFlowCompBackend - x_mat_tf: tf.Tensor = comp_be._norm_right(x_mat) - y_mat_tf: tf.Tensor = comp_be._norm_right(y_mat) + x_mat_tf: tf.Tensor = comp_be._get_tensor(x_mat) + y_mat_tf: tf.Tensor = comp_be._get_tensor(y_mat) with tf.device(device): x_mat_tf = tf.identity(x_mat_tf) @@ -248,7 +248,7 @@ def euclidean_dist( dists = tf.squeeze(tf.norm(tf.subtract(x_mat_tf, y_mat_tf), axis=-1)) dists = _unsqueeze_if_scalar(dists) - return comp_be._norm_left(dists) + return comp_be._cast_output(dists) @staticmethod def sqeuclidean_dist( @@ -274,7 +274,7 @@ def sqeuclidean_dist( """ dists = TensorFlowCompBackend.Metrics.euclidean_dist(x_mat, y_mat) squared: tf.Tensor = tf.math.square( - TensorFlowCompBackend._norm_right(dists) + TensorFlowCompBackend._get_tensor(dists) ) - return TensorFlowCompBackend._norm_left(squared) + return TensorFlowCompBackend._cast_output(squared) From 5fc272193efb067b59fb366ede160eea3b3510c2 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 10:32:35 +0100 Subject: [PATCH 59/70] docs: tft docstring Signed-off-by: anna-charlotte --- docarray/typing/tensor/tensorflow_tensor.py | 72 ++++++++++++++------- 1 file changed, 50 insertions(+), 22 deletions(-) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 0d558d59fe1..3b440c5080d 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -34,16 +34,64 @@ class metaTensorFlow( @_register_proto(proto_type_name='tensorflow_tensor') class TensorFlowTensor(AbstractTensor, Generic[ShapeT], metaclass=metaTensorFlow): """ - TensorFlowTensor class with a `.tensor` attribute of type `tf.Tensor`, intended for - use in a Document. + TensorFlowTensor class with a :attr:`~docarray.typing.TensorFlowTensor.tensor` + attribute of type :class:`tf.Tensor`, intended for use in a Document. + This enables (de)serialization from/to protobuf and json, data validation, and coersion from compatible types like numpy.ndarray. This type can also be used in a parametrized way, specifying the shape of the tensor. + In comparison to :class:`~docarray.typing.TorchTensor` and + :class:`~docarray.typing.NdArray`, :class:`~docarray.typing.TensorFlowTensor` is not + a subclass of :class:`tf.Tensor` (or :class:`torch.Tensor`, :class:`np.ndarray` + respectively). + Instead, the :class:`tf.Tensor` is stored in + :attr:`~docarray.typing.TensorFlowTensor.tensor`. + Therefore, to do operations on the actual tensor data you have to always access the + :attr:`~docarray.typing.TensorFlowTensor.tensor` attribute. + EXAMPLE USAGE + .. code-block:: python + + import tensorflow as tf + from docarray.typing import TensorFlowTensor + + + t = TensorFlowTensor(tensor=tf.zeros((224, 224))) + + # tensorflow functions + broadcasted = tf.broadcast_to(t.tensor, (3, 224, 224)) + broadcasted = tf.broadcast_to(t.unwrap(), (3, 224, 224)) + broadcasted = tf.broadcast_to(t, (3, 224, 224)) # this will fail + + # tensorflow.Tensor methods: + arr = t.tensor.numpy() + arr = t.unwrap().numpy() + arr = t.numpy() # this will fail + + The :class:`~docarray.computation.tensorflow_backend.TensorFlowBackend` however, + operates on our :class:`~docarray.typing.TensorFlowTensor` instances. + Here, you do not have to access the :attr:`~docarray.typing.TensorFlowTensor.tensor` + but can instead just hand over your :class:`~docarray.typing.TensorFlowTensor` + instance. + + .. code-block:: python + + import tensorflow as tf + from docarray.typing import TensorFlowTensor + + + zeros = TensorFlowTensor(tensor=tf.zeros((3, 224, 224))) + + comp_be = zeros.get_comp_backend() + reshaped = comp_be.reshape(zeros, (224, 224, 3)) + assert comp_be.shape(reshaped) == (224, 224, 3) + + You can use :class:`~docarray.typing.TensorFlowTensor` in a Document as follows: + .. code-block:: python from docarray import BaseDocument @@ -78,26 +126,6 @@ class MyDoc(BaseDocument): square_crop=tf.zeros((3, 128, 64)), # this will also fail validation ) - If you want to call functions provided by tensorflow you have to access the - `.tensor` attribute or call `.unwrap()` on your TensorFlowTensor instance: - - .. code-block:: python - from docarray.typing import TensorFlowTensor - import tensorflow as tf - - - t = TensorFlowTensor(tf.zeros((224, 224))) - - # tensorflow functions - broadcasted = tf.broadcast_to(t.tensor, (3, 224, 224)) - broadcasted = tf.broadcast_to(t.unwrap(), (3, 224, 224)) - broadcasted = tf.broadcast_to(t, (3, 224, 224)) # this will fail - - # tensorflow.Tensor methods: - arr = t.tensor.numpy() - arr = t.unwrap().numpy() - arr = t.numpy() # this will fail - """ __parametrized_meta__ = metaTensorFlow From 7432123bf601638391b2eb41f19068ebb28a2462 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 11:07:48 +0100 Subject: [PATCH 60/70] docs: add comment to array stacked tf Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index eeffb99160d..a3881924390 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -149,6 +149,9 @@ def _create_columns( columns: Dict[str, Union[DocumentArrayStacked, AbstractTensor]] = dict() for field, type_ in column_schema.items(): + # tensorflow does not allow item assignment, therefore the optimized way of + # initializing an empty array and assigning values to it iteratively does + # not work here, therefore handle separately. if tf_available and isinstance(getattr(docs[0], field), TensorFlowTensor): tf_stack = [] for i, doc in enumerate(docs): From 1144d6fc77d23ffe5e4844b089bded0dce5f1c75 Mon Sep 17 00:00:00 2001 From: Charlotte Gerhaher Date: Tue, 7 Feb 2023 11:09:50 +0100 Subject: [PATCH 61/70] fix: apply suggestion from code review Co-authored-by: samsja <55492238+samsja@users.noreply.github.com> Signed-off-by: Charlotte Gerhaher --- tests/integrations/typing/test_typing_proto.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index 9d5b8040ee3..9956607f28f 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -50,6 +50,8 @@ class Mymmdoc(BaseDocument): @pytest.mark.tensorflow +@pytest.mark.proto + def test_proto_all_types_proto3(): import tensorflow as tf From 25b9f42e1d2d424c2cc4a8c800de18789d8100b4 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 13:32:58 +0100 Subject: [PATCH 62/70] fix: apply suggestions from code review Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 21 +++++---------------- docarray/typing/tensor/tensorflow_tensor.py | 6 ++++++ tests/units/array/test_array_stacked_tf.py | 11 ++++++++++- 3 files changed, 21 insertions(+), 17 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index a3881924390..639908afd92 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -165,7 +165,8 @@ def _create_columns( columns[field] = TensorFlowTensor(stacked) for i, doc in enumerate(docs): val = getattr(doc, field) - val.tensor = columns[field][i] + x = columns[field][i].tensor + val.tensor = x elif issubclass(type_, AbstractTensor): tensor = getattr(docs[0], field) @@ -230,12 +231,7 @@ def __getitem__(self, item): # note this should handle slices doc = self._docs[item] # NOTE: this could be speed up by using a cache for field in self._columns.keys(): - value = self._columns[field] - if tf_available and isinstance(value, TensorFlowTensor): - new_value = value.tensor[item] - else: - new_value = value[item] - setattr(doc, field, new_value) + setattr(doc, field, self._columns[field][item]) return doc def _get_slice(self: T, item: slice) -> T: @@ -246,10 +242,7 @@ def _get_slice(self: T, item: slice) -> T: """ columns_sliced: Dict[str, AnyTensor] = {} for k, col in self._columns.items(): - if tf_available and isinstance(col, TensorFlowTensor): - columns_sliced[k] = TensorFlowTensor(col.tensor[item]) - else: - columns_sliced[k] = col[item] + columns_sliced[k] = col[item] columns_sliced_ = cast(Dict[str, Union[AbstractTensor, T]], columns_sliced) return self._from_columns(self._docs[item], columns_sliced_) @@ -305,11 +298,7 @@ def unstack(self: T) -> DocumentArray: """ for i, doc in enumerate(self._docs): for field in self._columns.keys(): - val = self._columns[field] - if tf_available and isinstance(val, TensorFlowTensor): - setattr(doc, field, val.tensor[i]) - else: - setattr(doc, field, val[i]) + setattr(doc, field, self._columns[field][i]) # NOTE: here we might need to copy the tensor # see here diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 3b440c5080d..36e1fbd34ed 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -134,6 +134,12 @@ def __init__(self, tensor: tf.Tensor): super().__init__() self.tensor = tensor + def __getitem__(self, item): + from docarray.computation.tensorflow_backend import TensorFlowCompBackend + + output = self.unwrap()[item] + return TensorFlowCompBackend._cast_output(t=output) + @classmethod def __get_validators__(cls): # one or more validators may be yielded which will be called in the diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 514a376a7cd..646c1b5c8c8 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -37,7 +37,16 @@ def test_len(batch): @pytest.mark.tensorflow def test_getitem(batch): for i in range(len(batch)): - assert tnp.allclose(batch[i].tensor.tensor, tf.zeros((3, 224, 224))) + item = batch[i] + assert isinstance(item.tensor, TensorFlowTensor) + assert tnp.allclose(item.tensor.tensor, tf.zeros((3, 224, 224))) + + +@pytest.mark.tensorflow +def test_get_slice(batch): + sliced = batch[0:2] + assert isinstance(sliced, DocumentArrayStacked) + assert len(sliced) == 2 @pytest.mark.tensorflow From 102e42aa52e0e1cd51f485188925c77c8c61ffbc Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 14:15:37 +0100 Subject: [PATCH 63/70] test: fix black formatting Signed-off-by: anna-charlotte --- tests/integrations/typing/test_typing_proto.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index 9956607f28f..7144ee007e1 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -51,7 +51,6 @@ class Mymmdoc(BaseDocument): @pytest.mark.tensorflow @pytest.mark.proto - def test_proto_all_types_proto3(): import tensorflow as tf From b4b7e4333c4c0952baea53889bbffcee1c54a0b0 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 15:53:51 +0100 Subject: [PATCH 64/70] fix: implement getitem setitem iter for tftensor Signed-off-by: anna-charlotte --- docarray/typing/tensor/tensorflow_tensor.py | 21 +++++++++++++++---- tests/units/array/test_array_stacked_tf.py | 1 + .../typing/tensor/test_tensor_flow_tensor.py | 9 ++++++++ 3 files changed, 27 insertions(+), 4 deletions(-) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index cdb89057e47..792310f5364 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -2,6 +2,7 @@ import numpy as np import tensorflow as tf # type: ignore +import tensorflow._api.v2.experimental.numpy as tnp from docarray.typing.proto_register import _register_proto from docarray.typing.tensor.abstract_tensor import AbstractTensor @@ -137,14 +138,26 @@ def __init__(self, tensor: tf.Tensor): def __getitem__(self, item): from docarray.computation.tensorflow_backend import TensorFlowCompBackend - output = self.unwrap()[item] - return TensorFlowCompBackend._cast_output(t=output) + tensor = self.unwrap() + if tensor is not None: + tensor = tensor[item] + return TensorFlowCompBackend._cast_output(t=tensor) def __setitem__(self, index, value): - """Set a slice of this tensor.""" + """Set a slice of this tensor's tf.Tensor""" + if tnp.all(tf.math.is_nan(value)): + self.tensor = None + else: + t = self.unwrap() + var = tf.Variable(t) + var[index].assign(value) + self.tensor = tf.constant(var) def __iter__(self): - """Iterate over the elements of this tensor.""" + """Iterate over the elements of this tensor's tf.Tensor.""" + tensor = self.unwrap() + for i in range(len(tensor)): + yield tensor[i] @classmethod def __get_validators__(cls): diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index b7c4570d31c..577866bc480 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -259,6 +259,7 @@ class MyDoc(BaseDocument): ).stack() assert 'tensor' in da._tensor_columns.keys() + assert da.tensor.tensor is None @pytest.mark.tensorflow diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index 28d1e94cb5c..e1727acabb9 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -167,3 +167,12 @@ def test_parametrized_operations(): assert isinstance(t_result, tf.Tensor) assert not isinstance(t_result, TensorFlowTensor) assert not isinstance(t_result, TensorFlowTensor[128]) + + +@pytest.mark.tensorflow +def test_set_item(): + t = TensorFlowTensor(tensor=tf.zeros((3, 224, 224))) + t[0] = tf.ones((1, 224, 224)) + assert tnp.allclose(t.tensor[0], tf.ones((1, 224, 224))) + assert tnp.allclose(t.tensor[1], tf.zeros((1, 224, 224))) + assert tnp.allclose(t.tensor[2], tf.zeros((1, 224, 224))) From 545438dc74fe706e4cb0dc6b80c725c7dbd14a98 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Tue, 7 Feb 2023 16:02:12 +0100 Subject: [PATCH 65/70] docs: readme Signed-off-by: anna-charlotte --- README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index 8c9039e8391..2879f87e362 100644 --- a/README.md +++ b/README.md @@ -277,6 +277,13 @@ You instantly win in code readability and maintainability. And for the same pric schema definition (see below). Everything handles in a pythonic manner by relying on type hints. +## Coming from TensorFlow + +To use DocArray with tensorflow we first need to install the following extras: +``` +pip install tensorflow==2.11.0 +pip install protobuf==3.19.0 +``` ## Coming from FastAPI From c2aa0b1dfa1e09b0493c71e9692c9019ad828513 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 8 Feb 2023 09:40:03 +0100 Subject: [PATCH 66/70] docs: update readme.md Signed-off-by: anna-charlotte --- README.md | 111 ++++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 96 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 2879f87e362..ad820331e5f 100644 --- a/README.md +++ b/README.md @@ -209,22 +209,22 @@ class MyMultiModalModel(nn.Module): self.text_encoder = TextEncoder() def forward(self, text_1, text_2, image_1, image_2, audio_1, audio_2): - emnedding_text_1 = self.text_encoder(text_1) - emnedding_text_2 = self.text_encoder(text_2) + embedding_text_1 = self.text_encoder(text_1) + embedding_text_2 = self.text_encoder(text_2) - emnedding_image_1 = self.image_encoder(image_1) - emnedding_image_2 = self.image_encoder(image_2) + embedding_image_1 = self.image_encoder(image_1) + embedding_image_2 = self.image_encoder(image_2) - emnedding_audio_1 = self.image_encoder(audio_1) - emnedding_audio_2 = self.image_encoder(audio_2) + embedding_audio_1 = self.image_encoder(audio_1) + embedding_audio_2 = self.image_encoder(audio_2) return ( - emnedding_text_1, - emnedding_text_2, - emnedding_image_1, - emnedding_image_2, - emnedding_audio_1, - emnedding_audio_2, + embedding_text_1, + embedding_text_2, + embedding_image_1, + embedding_image_2, + embedding_audio_1, + embedding_audio_2, ) ``` @@ -258,14 +258,14 @@ class MyPodcastModel(nn.Module): self.image_encoder = ImageEncoder() self.text_encoder = TextEncoder() - def forward_podcast(da: DocumentArray[Podcast]) -> DocumentArray[Podcast]: + def forward_podcast(self, da: DocumentArray[Podcast]) -> DocumentArray[Podcast]: da.audio.embedding = self.audio_encoder(da.audio.tensor) da.text.embedding = self.text_encoder(da.text.tensor) da.image.embedding = self.image_encoder(da.image.tensor) return da - def forward(da: DocumentArray[PairPodcast]) -> DocumentArray[PairPodcast]: + def forward(self, da: DocumentArray[PairPodcast]) -> DocumentArray[PairPodcast]: da.left = self.forward_podcast(da.left) da.right = self.forward_podcast(da.right) @@ -279,12 +279,93 @@ schema definition (see below). Everything handles in a pythonic manner by relyin ## Coming from TensorFlow -To use DocArray with tensorflow we first need to install the following extras: +Similar to the PyTorch approach, you can also use DocArray with TensorFlow to handle and represent multi-modal data inside your ML model. + +First off, to use DocArray with TensorFlow we first need to install it as follows: ``` pip install tensorflow==2.11.0 pip install protobuf==3.19.0 ``` +Now, lets look at an example for TensorFlow without using DocArray: + +```python +import tensorflow as tf + + +class MyMultiModalModel(tf.keras.Model): + def __init__(self): + super().__init__() + self.audio_encoder = AudioEncoder() + self.image_encoder = ImageEncoder() + self.text_encoder = TextEncoder() + + def call(self, inputs, training=None, mask=None): + embedding_text_1 = self.text_encoder(inputs[0]) + embedding_text_2 = self.text_encoder(inputs[1]) + + embedding_image_1 = self.image_encoder(inputs[2]) + embedding_image_2 = self.image_encoder(inputs[3]) + + embedding_audio_1 = self.image_encoder(inputs[4]) + embedding_audio_2 = self.image_encoder(inputs[5]) + + return ( + embedding_text_1, + embedding_text_2, + embedding_image_1, + embedding_image_2, + embedding_audio_1, + embedding_audio_2, + ) +``` + +Not the most readable option if you ask us. Let's take a look at the same example while using DocArray: + +```python +from docarray import DocumentArray, BaseDocument +from docarray.documents import Image, Text, Audio + +import tensorflow as tf + + +class Podcast(BaseDocument): + text: Text + image: Image + audio: Audio + + +class PairPodcast(BaseDocument): + left: Podcast + right: Podcast + + +class MyPodcastModel(tf.keras.Model): + def __init__(self): + super().__init__() + self.audio_encoder = AudioEncoder() + self.image_encoder = ImageEncoder() + self.text_encoder = TextEncoder() + + def forward_podcast(self, da: DocumentArray[Podcast]) -> DocumentArray[Podcast]: + da.audio.embedding = self.audio_encoder( + da.audio.tensor.tensor + ) # get TensorFlowTensor's .tensor attr + da.text.embedding = self.text_encoder(da.text.tensor.tensor) + da.image.embedding = self.image_encoder(da.image.tensor.tensor) + + return da + + def call(self, inputs: DocumentArray[PairPodcast]) -> DocumentArray[PairPodcast]: + inputs.left = self.forward_podcast(inputs.left) + inputs.right = self.forward_podcast(inputs.right) + + return inputs +``` + +Much nicer, don't you think? One main difference to using DocArray with PyTorch, is that when using TensorFlowTensor's, you have to access it's `.tensor` attribute directly, as it can be seen in `.forward_podcast()` above. This is due to the fact that while `TorchTensor` is a subclass of `torch.Tensor`, `TensorFlowTensor` is not a subclass of `tf.Tensor` but instead stores a `tf.Tensor` in its `.tensor` attribute. + + ## Coming from FastAPI Documents are Pydantic Models (with a twist), and as such they are fully compatible with FastAPI: From 81a2540ed1afc146c515a191d0691c0b88d7bd4a Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 8 Feb 2023 09:46:41 +0100 Subject: [PATCH 67/70] fix: remove n dim from abstract method instead use comp be Signed-off-by: anna-charlotte --- docarray/array/array_stacked.py | 3 ++- docarray/typing/tensor/abstract_tensor.py | 6 ------ docarray/typing/tensor/tensorflow_tensor.py | 2 +- 3 files changed, 3 insertions(+), 8 deletions(-) diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index 533228a6103..05c6c4762aa 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -206,7 +206,8 @@ def _create_columns( # We thus chose to convert the individual rank 0 tensors to rank 1 # This does mean that stacking rank 0 tensors will transform them # to rank 1 - if tensor_columns[field].ndim == 1: + tensor = tensor_columns[field] + if tensor.get_comp_backend().n_dim(tensor) == 1: setattr(doc, field, tensor_columns[field][i : i + 1]) else: setattr(doc, field, tensor_columns[field][i]) diff --git a/docarray/typing/tensor/abstract_tensor.py b/docarray/typing/tensor/abstract_tensor.py index 8c2a772e95a..c2451fa3272 100644 --- a/docarray/typing/tensor/abstract_tensor.py +++ b/docarray/typing/tensor/abstract_tensor.py @@ -265,9 +265,3 @@ def _docarray_to_json_compatible(self): :return: a representation of the tensor compatible with orjson """ ... - - @property - @abc.abstractmethod - def ndim(self) -> int: - """The number of dimensions / rank of this tensor.""" - ... diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 792310f5364..61b4a29a5e5 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -2,7 +2,7 @@ import numpy as np import tensorflow as tf # type: ignore -import tensorflow._api.v2.experimental.numpy as tnp +import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray.typing.proto_register import _register_proto from docarray.typing.tensor.abstract_tensor import AbstractTensor From 838955a1878e71ffc58083cb5cfda9e2e5edb1cc Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 8 Feb 2023 09:48:08 +0100 Subject: [PATCH 68/70] fix: remove proto mark, because only test for proto 3 here Signed-off-by: anna-charlotte --- tests/integrations/typing/test_typing_proto.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/integrations/typing/test_typing_proto.py b/tests/integrations/typing/test_typing_proto.py index 7144ee007e1..9d5b8040ee3 100644 --- a/tests/integrations/typing/test_typing_proto.py +++ b/tests/integrations/typing/test_typing_proto.py @@ -50,7 +50,6 @@ class Mymmdoc(BaseDocument): @pytest.mark.tensorflow -@pytest.mark.proto def test_proto_all_types_proto3(): import tensorflow as tf From 09dd6a9deeffbcddb3b744021437b9af040e2d3e Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 8 Feb 2023 10:13:54 +0100 Subject: [PATCH 69/70] fix: tf set item and add tests Signed-off-by: anna-charlotte --- docarray/typing/tensor/tensorflow_tensor.py | 13 +++++-------- tests/units/array/test_array_stacked_tf.py | 1 - 2 files changed, 5 insertions(+), 9 deletions(-) diff --git a/docarray/typing/tensor/tensorflow_tensor.py b/docarray/typing/tensor/tensorflow_tensor.py index 61b4a29a5e5..d004650b630 100644 --- a/docarray/typing/tensor/tensorflow_tensor.py +++ b/docarray/typing/tensor/tensorflow_tensor.py @@ -2,7 +2,6 @@ import numpy as np import tensorflow as tf # type: ignore -import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray.typing.proto_register import _register_proto from docarray.typing.tensor.abstract_tensor import AbstractTensor @@ -145,13 +144,11 @@ def __getitem__(self, item): def __setitem__(self, index, value): """Set a slice of this tensor's tf.Tensor""" - if tnp.all(tf.math.is_nan(value)): - self.tensor = None - else: - t = self.unwrap() - var = tf.Variable(t) - var[index].assign(value) - self.tensor = tf.constant(var) + t = self.unwrap() + value = tf.cast(value, dtype=t.dtype) + var = tf.Variable(t) + var[index].assign(value) + self.tensor = tf.constant(var) def __iter__(self): """Iterate over the elements of this tensor's tf.Tensor.""" diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index 577866bc480..b7c4570d31c 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -259,7 +259,6 @@ class MyDoc(BaseDocument): ).stack() assert 'tensor' in da._tensor_columns.keys() - assert da.tensor.tensor is None @pytest.mark.tensorflow From 85183ecd7ba0bf3c667375a44e08ef86afdd4d69 Mon Sep 17 00:00:00 2001 From: anna-charlotte Date: Wed, 8 Feb 2023 14:57:45 +0100 Subject: [PATCH 70/70] docs: update tf section in readme.md Signed-off-by: anna-charlotte --- README.md | 69 ++++++++++--------------------------------------------- 1 file changed, 12 insertions(+), 57 deletions(-) diff --git a/README.md b/README.md index ad820331e5f..90034909ba6 100644 --- a/README.md +++ b/README.md @@ -287,83 +287,38 @@ pip install tensorflow==2.11.0 pip install protobuf==3.19.0 ``` -Now, lets look at an example for TensorFlow without using DocArray: +Compared to using DocArray with PyTorch, there is one main difference when using it with TensorFlow:\ +While DocArray's `TorchTensor` is a subclass of `torch.Tensor`, this is not the case for the `TensorFlowTensor`: Due to technical limitations on `tf.Tensor`, docarray's `TensorFlowTensor` is not a subclass of `tf.Tensor` but instead stores a `tf.Tensor` in its `.tensor` attribute. -```python -import tensorflow as tf - - -class MyMultiModalModel(tf.keras.Model): - def __init__(self): - super().__init__() - self.audio_encoder = AudioEncoder() - self.image_encoder = ImageEncoder() - self.text_encoder = TextEncoder() - - def call(self, inputs, training=None, mask=None): - embedding_text_1 = self.text_encoder(inputs[0]) - embedding_text_2 = self.text_encoder(inputs[1]) - - embedding_image_1 = self.image_encoder(inputs[2]) - embedding_image_2 = self.image_encoder(inputs[3]) - - embedding_audio_1 = self.image_encoder(inputs[4]) - embedding_audio_2 = self.image_encoder(inputs[5]) - - return ( - embedding_text_1, - embedding_text_2, - embedding_image_1, - embedding_image_2, - embedding_audio_1, - embedding_audio_2, - ) -``` +How does this effect you? Whenever you want to access the tensor data to e.g. do operations with it or hand it to your ML model, instead of handing over your `TensorFlowTensor` instance, you need to access its `.tensor` attribute. -Not the most readable option if you ask us. Let's take a look at the same example while using DocArray: +This would look like the following: ```python +from typing import Optional + from docarray import DocumentArray, BaseDocument -from docarray.documents import Image, Text, Audio import tensorflow as tf class Podcast(BaseDocument): - text: Text - image: Image - audio: Audio - - -class PairPodcast(BaseDocument): - left: Podcast - right: Podcast + audio_tensor: Optional[AudioTensorFlowTensor] + embedding: Optional[AudioTensorFlowTensor] class MyPodcastModel(tf.keras.Model): def __init__(self): super().__init__() self.audio_encoder = AudioEncoder() - self.image_encoder = ImageEncoder() - self.text_encoder = TextEncoder() - - def forward_podcast(self, da: DocumentArray[Podcast]) -> DocumentArray[Podcast]: - da.audio.embedding = self.audio_encoder( - da.audio.tensor.tensor - ) # get TensorFlowTensor's .tensor attr - da.text.embedding = self.text_encoder(da.text.tensor.tensor) - da.image.embedding = self.image_encoder(da.image.tensor.tensor) - - return da - - def call(self, inputs: DocumentArray[PairPodcast]) -> DocumentArray[PairPodcast]: - inputs.left = self.forward_podcast(inputs.left) - inputs.right = self.forward_podcast(inputs.right) + def call(self, inputs: DocumentArray[Podcast]) -> DocumentArray[Podcast]: + inputs.audio_tensor.embedding = self.audio_encoder( + inputs.audio_tensor.tensor + ) # access audio_tensor's .tensor attribute return inputs ``` -Much nicer, don't you think? One main difference to using DocArray with PyTorch, is that when using TensorFlowTensor's, you have to access it's `.tensor` attribute directly, as it can be seen in `.forward_podcast()` above. This is due to the fact that while `TorchTensor` is a subclass of `torch.Tensor`, `TensorFlowTensor` is not a subclass of `tf.Tensor` but instead stores a `tf.Tensor` in its `.tensor` attribute. ## Coming from FastAPI