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`

.

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]]

Args | |
---|---|

`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). |

Returns | |
---|---|

A `Tensor` . Has the same type as `data` . |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/SegmentMax