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| 1 | +SegmentMax |
| 2 | +========== |
| 3 | + |
| 4 | + |
| 5 | +.. meta:: |
| 6 | + :description: Learn about SegmentMax-16 - an arithmetic operation which computes the maximum values along segments of a tensor. |
| 7 | + |
| 8 | +**Versioned name**: *SegmentMax-16* |
| 9 | + |
| 10 | +**Category**: *Arithmetic* |
| 11 | + |
| 12 | +**Short description**: *SegmentMax-16* operation finds the maximum value in each specified segment of the ``input`` tensor. |
| 13 | + |
| 14 | +**Detailed description** |
| 15 | + |
| 16 | +For each index in ``segment_ids`` the operator gets values from ``data`` input tensor and calculates the maximum value for each segment. |
| 17 | + |
| 18 | +For example ``segments_ids`` with value ``[0,0,0,1,1,3,5,5]`` defines 4 non-empty segments. ``num_segments`` is not given. When coupled with a 1D data tensor ``data``, the segments are as follows: |
| 19 | + |
| 20 | +* Segment_0: ``[data[0], data[1], data[2]]`` |
| 21 | +* Segment_1: ``[data[3], data[4]]`` |
| 22 | +* Segment_2: ``[]`` |
| 23 | +* Segment_3: ``[data[5]]`` |
| 24 | +* Segment_4: ``[]`` |
| 25 | +* Segment_5: ``[data[6], data[7]]`` |
| 26 | + |
| 27 | +When there are no values in a segment, ``output[segment]`` is defined by ``fill_mode`` attribute. |
| 28 | + |
| 29 | +For ``fill_mode`` equal to ``ZERO`` , the operation output would be ``[max(Segment_0), max(Segment_1), 0, max(Segment_3), 0, max(Segment_5)]``. |
| 30 | + |
| 31 | +**Attributes**: |
| 32 | + |
| 33 | +* **1**: *fill_mode* |
| 34 | + |
| 35 | + * **Description**: Responsible for the value assigned to segments which are empty. **Required.** |
| 36 | + * **Range of values**: Name of the mode in string format: |
| 37 | + |
| 38 | + * ``ZERO`` - the empty segments are filled with zeros. |
| 39 | + * ``LOWEST`` - the empty segments are filled with the lowest value of the data type *T*. |
| 40 | + * **Type**: ``string`` |
| 41 | + |
| 42 | +**Inputs** |
| 43 | + |
| 44 | +* **1**: ``data`` - ND tensor of type *T*, the numerical data on which SegmentMax operation will be performed. **Required.** |
| 45 | + |
| 46 | +* **2**: ``segment_ids`` - 1D Tensor of sorted non-negative numbers of type *T_IDX1*. Its size is equal to the size of the first dimension of the ``data`` input tensor. **Required.** |
| 47 | + |
| 48 | +* **3**: ``num_segments`` - A scalar value of type *T_IDX2* representing the segments count. If ``num_segments < max(segment_ids) + 1`` then the extra segments defined in ``segment_ids`` are not included in the output. If If ``num_segments > max(segment_ids) + 1`` then the output is padded with empty segments. Defaults to ``max(segment_ids) + 1``. **Optional.** |
| 49 | + |
| 50 | +**Outputs** |
| 51 | + |
| 52 | +* **1**: The output tensor has same rank and dimensions as the ``data`` input tensor except for the first dimension which is equal to the value of ``num_segments``. |
| 53 | + |
| 54 | +**Types** |
| 55 | + |
| 56 | +* *T*: any supported numerical data type. |
| 57 | +* *T_IDX1*, *T_IDX2*: ``int64`` or ``int32``. |
| 58 | + |
| 59 | +**Examples** |
| 60 | + |
| 61 | +*Example 1: num_segments < max(segment_ids) + 1* |
| 62 | + |
| 63 | +.. code-block:: xml |
| 64 | + :force: |
| 65 | +
|
| 66 | + <layer ... type="SegmentMax" ... > |
| 67 | + <data empty_segment_value="ZERO"> |
| 68 | + <input> |
| 69 | + <port id="0" precision="F32"> <!-- data --> |
| 70 | + <dim>5</dim> |
| 71 | + </port> |
| 72 | + <port id="1" precision="I32"> <!-- segment_ids with 4 segments: [0, 0, 2, 3, 3] --> |
| 73 | + <dim>5</dim> |
| 74 | + </port> |
| 75 | + <port id="2" precision="I64"> <!-- number of segments: 2 --> |
| 76 | + <dim>0</dim> |
| 77 | + </port> |
| 78 | + </input> |
| 79 | + <output> |
| 80 | + <port id="3" precision="F32"> |
| 81 | + <dim>2</dim> |
| 82 | + </port> |
| 83 | + </output> |
| 84 | + </layer> |
| 85 | +
|
| 86 | +*Example 2: num_segments > max(segment_ids) + 1* |
| 87 | + |
| 88 | +.. code-block:: xml |
| 89 | + :force: |
| 90 | +
|
| 91 | + <layer ... type="SegmentMax" ... > |
| 92 | + <data empty_segment_value="ZERO"> |
| 93 | + <input> |
| 94 | + <port id="0" precision="F32"> <!-- data --> |
| 95 | + <dim>5</dim> |
| 96 | + </port> |
| 97 | + <port id="1" precision="I32"> <!-- segment_ids with 4 segments: [0, 0, 2, 3, 3] --> |
| 98 | + <dim>5</dim> |
| 99 | + </port> |
| 100 | + <port id="2" precision="I64"> <!-- number of segments: 8 --> |
| 101 | + <dim>0</dim> |
| 102 | + </port> |
| 103 | + </input> |
| 104 | + <output> |
| 105 | + <port id="3" precision="F32"> |
| 106 | + <dim>8</dim> |
| 107 | + </port> |
| 108 | + </output> |
| 109 | + </layer> |
| 110 | +
|
| 111 | +*Example 3: 2D input data, no num_segments* |
| 112 | + |
| 113 | +.. code-block:: xml |
| 114 | + :force: |
| 115 | +
|
| 116 | + <layer ... type="SegmentMax" ... > |
| 117 | + <data empty_segment_value="LOWEST"> |
| 118 | + <input> |
| 119 | + <port id="0" precision="I32"> <!-- data --> |
| 120 | + <dim>3</dim> |
| 121 | + <dim>4</dim> |
| 122 | + </port> |
| 123 | + <port id="1" precision="I64"> <!-- segment_ids with 2 segments: [0, 1, 1] --> |
| 124 | + <dim>3</dim> |
| 125 | + </port> |
| 126 | + </input> |
| 127 | + <output> |
| 128 | + <port id="2" precision="I32"> |
| 129 | + <dim>2</dim> |
| 130 | + <dim>4</dim> |
| 131 | + </port> |
| 132 | + </output> |
| 133 | + </layer> |
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