tf.raw_ops.SegmentMax

Computes the maximum along segments of a tensor.

tf.raw_ops.SegmentMax(
    data, segment_ids, name=None
)

Read the section on segmentation for an explanation of segments.

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

If the max 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.segment_max(c, tf.constant([0, 0, 1]))
# ==> [[4, 3, 3, 4],
#      [5, 6, 7, 8]]

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.
name A name for the operation (optional).

A Tensor. Has the same type as data.