From ceb3d153b19235d7f5807b7bfa0aecfc8c79bfa8 Mon Sep 17 00:00:00 2001 From: p-wysocki Date: Thu, 23 Jan 2025 11:48:34 +0100 Subject: [PATCH] Apply CR Signed-off-by: p-wysocki --- .../arithmetic/segment-max-16.rst | 32 ++++++++++--------- 1 file changed, 17 insertions(+), 15 deletions(-) diff --git a/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/arithmetic/segment-max-16.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/arithmetic/segment-max-16.rst index c09ad415313c5f..e29dcf73d7e23a 100644 --- a/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/arithmetic/segment-max-16.rst +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/arithmetic/segment-max-16.rst @@ -1,5 +1,5 @@ SegmentMax -=================== +========== .. meta:: @@ -24,32 +24,29 @@ For example ``segments_ids`` with value ``[0,0,0,1,1,3,5,5]`` defines 4 non-empt * Segment_4: ``[]`` * Segment_5: ``[data[6], data[7]]`` -When there are no values in a segment, ``output[segment]`` is set to 0. +When there are no values in a segment, ``output[segment]`` is defined by ``empty_segment_value`` input. In that case, the output would be ``[max(Segment_0), max(Segment_1), 0, max(Segment_3), 0, max(Segment_5)]``. **Attributes**: -SegmentMax-16 has no attributes. +* **1**: *empty_segment_value* -**Inputs** + * **Description**: The value assigned to segments which are empty. **Required.** + * **Range of values**: A scalar. + * **Type**: *T* -* **1**: *data* +**Inputs** - * **Description**: The numerical data on which SegmentMax operation will be performed. **Required.** - * **Range of values**: An ND tensor of type *T*. - * **Type**: *T* +* **1**: ``data`` - ND tensor of type *T*, the numerical data on which SegmentMax operation will be performed. **Required.** -* **2**: *segment_ids* +* **2**: ``segment_ids`` - 1D Tensor of sorted non-negative numbers of type *T_IDX*. Its size is equal to the size of the first dimension of the ``data`` input tensor. The values must be smaller than ``num_segments``. **Required.** - * **Description**: Controls how the data is divided into segments. **Required.** - * **Range of values**: 1D tensor of non-negative, sorted integer numbers. Its size is equal to the size of the first dimension of the input tensor. - * **Type**: *T_IDX* +* **4**: ``num_segments`` - A scalar value of type *T_IDX* representing the segments count, used for shape inference. **Optional.** **Outputs** -* **1**: The output tensor of type *T* and almost the same shape as the ``data`` input tensor with the exception for the first dimension, which is equal to the count of unique segment IDs (calculated as ``max(segment_ids) + 1``). - +* **1**: The output tensor has same rank and dimensions as the ``data`` input tensor except for the first dimension which is calculated as ``max(segment_ids) + 1`` **Types** * *T*: any supported numerical data type. @@ -63,6 +60,7 @@ SegmentMax-16 has no attributes. :force: + 8 @@ -70,9 +68,12 @@ SegmentMax-16 has no attributes. 8 + + 0 + - + 4 @@ -84,6 +85,7 @@ SegmentMax-16 has no attributes. :force: + 3