o Ne%@slddlmZmZddlmZddlmZmZddlm Z m Z gZ dddZ ddd Z dd d Zdd d ZdS)) LayerHelper_non_static_mode)check_variable_and_dtype)_C_ops _legacy_C_ops)_in_legacy_dygraphin_dygraph_modeNcCtr t||ddStrt||dd\}}|St|dddt|dddtdit}|j|j d }|j|j d }|j d||d ||d ddid |S)at 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) #Outputs: [[4., 4., 4.], [4., 5., 6.]] ZSUMrpooltypeXZfloat32Zfloat64int32int64Zfloat16 segment_pool SegmentIdsr r segment_sumdtyper rZOutZ SummedIdstypeZinputsZoutputsattrsN)r rrrrrrrlocalsZ"create_variable_for_type_inferencerZ append_opdataZ segment_idsnameouttmphelperZ summed_idsr"ED:\Projects\ConvertPro\env\Lib\site-packages\paddle/geometric/math.pyrs4rcCr )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) #Outputs: [[2., 2., 2.], [4., 5., 6.]] ZMEANrr r r rrr segment_meanrrrrN)r$rrr"r"r#r$Ss4 r$cCr )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) #Outputs: [[1., 2., 1.], [4., 5., 6.]] ZMINrr r r rrr segment_minrrrrN)r%rrr"r"r#r%4r%cCr )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) #Outputs: [[3., 2., 3.], [4., 5., 6.]] MAXrr r r rrr segment_maxrrrrN)r(rrr"r"r#r(r&r()N)Zpaddle.fluid.layer_helperrrZpaddle.fluid.data_feederrZpaddlerrZpaddle.fluid.frameworkrr__all__rr$r%r(r"r"r"r#s   < >=