tf.math.segment_min

Computes the minimum along segments of a tensor.

tf.math.segment_min(
    data: Annotated[Any, tf.raw_ops.Any],
    segment_ids: Annotated[Any, tf.raw_ops.Any],
    name=None
) -> Annotated[Any, tf.raw_ops.Any]

Read the section on segmentation for an explanation of segments.

Computes a tensor such that \(output_i = \min_j(data_j)\) where min is over j such that segment_ids[j] == i.

If the min is empty for a given segment ID i, output[i] = 0.

For example:

c = tf.constant([[1,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.math.segment_min(c, tf.constant([0, 0, 1])).numpy()
array([[1, 2, 2, 1],
       [5, 6, 7, 8]], dtype=int32)

data A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. segment_ids A Tensor. Must be one of the following types: int32, int64. A 1-D tensor whose size is equal to the size of data's first dimension. Values should be sorted and can be repeated.

A Tensor. Has the same type as data.