tf.compat.v1.py_func

Wraps a python function and uses it as a TensorFlow op.

tf.compat.v1.py_func(
    func, inp, Tout, stateful=True, name=None
)

Migrate to TF2

This name was deprecated and removed in TF2, but tf.numpy_function is a near-exact replacement, just drop the stateful argument (all tf.numpy_function calls are considered stateful). It is compatible with eager execution and tf.function.

tf.py_function is a close but not an exact replacement, passing TensorFlow tensors to the wrapped function instead of NumPy arrays, which provides gradients and can take advantage of accelerators.

Before:

def fn_using_numpy(x):
  x[0] = 0.
  return x
tf.compat.v1.py_func(fn_using_numpy, inp=[tf.constant([1., 2.])],
    Tout=tf.float32, stateful=False)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([0., 2.], dtype=float32)>

After:

tf.numpy_function(fn_using_numpy, inp=[tf.constant([1., 2.])],
    Tout=tf.float32)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([0., 2.], dtype=float32)>