\;j%XddlmZddlmZddlmZddlmZgZd dZ d dZ d dZ d d Z y) )_C_ops)check_variable_and_dtype) LayerHelper)in_dynamic_or_pir_modeNcPtrtj||dSt|dddt|dddt d it }|j |j}|j |j}|jd||d||d d di |S) a Segment Sum Operator. This operator sums the elements of input `data` which with the same index in `segment_ids`. It computes a tensor such that $out_i = \\sum_{j} data_{j}$ where sum is over j such that `segment_ids[j] == i`. Args: data (Tensor): A tensor, available data type float32, float64, int32, int64, float16. segment_ids (Tensor): A 1-D tensor, which have the same size with the first dimension of input data. Available data type is int32, int64. name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: - output (Tensor), the reduced result. Examples: .. code-block:: python >>> import paddle >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32') >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32') >>> out = paddle.geometric.segment_sum(data, segment_ids) >>> print(out.numpy()) [[4. 4. 4.] [4. 5. 6.]] SUMXfloat32float64int32int64float16uint16 segment_pool SegmentIdsr rdtyper rOut SummedIdspooltypetypeinputsoutputsattrs) segment_sum rrrrrlocals"create_variable_for_type_inferencer append_opdata segment_idsnamehelperout summed_idss ^G:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\paddle/geometric/math.pyr r s@""4e<<   I   ! '9> 7fh777djj7I>>TZZ>P [9j9u%   cPtrtj||dSt|dddt|dddt d it }|j |j}|j |j}|jd||d||d d di |S) a Segment mean Operator. This operator calculate the mean value of input `data` which with the same index in `segment_ids`. It computes a tensor such that $out_i = \\frac{1}{n_i} \\sum_{j} data[j]$ where sum is over j such that 'segment_ids[j] == i' and $n_i$ is the number of all index 'segment_ids[j] == i'. Args: data (tensor): a tensor, available data type float32, float64, int32, int64, float16. segment_ids (tensor): a 1-d tensor, which have the same size with the first dimension of input data. available data type is int32, int64. name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: - output (Tensor), the reduced result. Examples: .. code-block:: python >>> import paddle >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32') >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32') >>> out = paddle.geometric.segment_mean(data, segment_ids) >>> print(out.numpy()) [[2. 2. 2.] [4. 5. 6.]] MEANr r rrrrrrrr) segment_meanr!r%s r,r0r0PsD""4f==   I   ! '9> 8vx877djj7I>>TZZ>P [9j9v&   r-cPtrtj||dSt|dddt|dddt d it }|j |j}|j |j}|jd||d||d d di |S) a Segment min operator. This operator calculate the minimum elements of input `data` which with the same index in `segment_ids`. It computes a tensor such that $out_i = \\min_{j} data_{j}$ where min is over j such that `segment_ids[j] == i`. Args: data (tensor): a tensor, available data type float32, float64, int32, int64, float16. segment_ids (tensor): a 1-d tensor, which have the same size with the first dimension of input data. available data type is int32, int64. name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: - output (Tensor), the reduced result. Examples: .. code-block:: python >>> import paddle >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32') >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32') >>> out = paddle.geometric.segment_min(data, segment_ids) >>> print(out.numpy()) [[1. 2. 1.] [4. 5. 6.]] MINr r rrrrrrrr) segment_minr!r%s r,r3r3B""4e<<   I   ! '9> 7fh777djj7I>>TZZ>P [9j9u%   r-cPtrtj||dSt|dddt|dddt d it }|j |j}|j |j}|jd||d||d d di |S) a Segment max operator. This operator calculate the maximum elements of input `data` which with the same index in `segment_ids`. It computes a tensor such that $out_i = \\max_{j} data_{j}$ where max is over j such that `segment_ids[j] == i`. Args: data (tensor): a tensor, available data type float32, float64, int32, int64, float16. segment_ids (tensor): a 1-d tensor, which have the same size with the first dimension of input data. available data type is int32, int64. name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: - output (Tensor), the reduced result. Examples: .. code-block:: python >>> import paddle >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32') >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32') >>> out = paddle.geometric.segment_max(data, segment_ids) >>> print(out.numpy()) [[3. 2. 3.] [4. 5. 6.]] MAXr r rrrrrrrr) segment_maxr!r%s r,r7r7r4r-)N) paddlerpaddle.base.data_feederrpaddle.base.layer_helperrpaddle.frameworkr__all__r r0r3r7r-r,r>s/<03 6r8v7t7r-