o "j$@s`ddlmZddlmZddlmZddlmZgZdddZ ddd Z dd d Z dd d Z dS))_C_ops)check_variable_and_dtype) LayerHelper)in_dynamic_or_pir_modeNcCtr t||dSt|dddt|dddtdit}|j|jd}|j|jd}|jd||d ||d d did |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.]] ZSUMXZfloat32Zfloat64int32int64Zfloat16Zuint16 segment_pool SegmentIdsr r segment_sumdtyperr ZOutZ SummedIdspooltypetypeZinputsZoutputsattrsN)r rrr rrlocalsZ"create_variable_for_type_inferencerZ append_opdataZ segment_idsnamehelperoutZ summed_idsrV/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddle/geometric/math.pyrs* rcCr)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.]] ZMEANrrr r r segment_meanrrrrrN)r rrrrrr Ps*"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) >>> print(out.numpy()) [[1. 2. 1.] [4. 5. 6.]] ZMINrrr r r segment_minrrrrrN)r!rrrrrr!*!r!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) >>> print(out.numpy()) [[3. 2. 3.] [4. 5. 6.]] MAXrrr r r segment_maxrrrrrN)r$rrrrrr$r"r$)N) ZpaddlerZpaddle.base.data_feederrZpaddle.base.layer_helperrZpaddle.frameworkr__all__rr r!r$rrrrs      9 ;: