diff --git a/docs/api/api_python/mindspore.ops.functional.rst b/docs/api/api_python/mindspore.ops.functional.rst index d92d9518e4f..6782ab813ba 100644 --- a/docs/api/api_python/mindspore.ops.functional.rst +++ b/docs/api/api_python/mindspore.ops.functional.rst @@ -473,6 +473,7 @@ Array操作 mindspore.ops.dense_to_sparse_coo mindspore.ops.dense_to_sparse_csr + mindspore.ops.csr_softmax mindspore.ops.csr_to_coo mindspore.ops.sparse_add diff --git a/docs/api/api_python/ops/mindspore.ops.func_csr_softmax.rst b/docs/api/api_python/ops/mindspore.ops.func_csr_softmax.rst new file mode 100644 index 00000000000..5c234079af2 --- /dev/null +++ b/docs/api/api_python/ops/mindspore.ops.func_csr_softmax.rst @@ -0,0 +1,19 @@ +mindspore.ops.csr_softmax +================================= + +.. py:function:: mindspore.ops.csr_softmax(logits, dtype) + + 计算 CSRTensorMatrix 的 softmax 。 + + 参数： + - **logits** （CSRTensor） - 输入稀疏的 CSRTensor。 + - **dtype** （dtype） - 输入的数据类型。 + + 返回： + - **CSRTensor** （CSRTensor） - 一个 csr_tensor 包含 + + - **indptr** - 指示每行中非零值的起始点和结束点。 + - **indices** - 输入中所有非零值的列位置。 + - **values** - 稠密张量的非零值。 + - **shape** - csrtensor 的形状. + \ No newline at end of file diff --git a/docs/api/api_python_en/mindspore.ops.functional.rst b/docs/api/api_python_en/mindspore.ops.functional.rst index 20e084f5943..2a36c560d0d 100644 --- a/docs/api/api_python_en/mindspore.ops.functional.rst +++ b/docs/api/api_python_en/mindspore.ops.functional.rst @@ -476,6 +476,7 @@ Sparse Functions mindspore.ops.dense_to_sparse_coo mindspore.ops.dense_to_sparse_csr mindspore.ops.csr_to_coo + mindspore.ops.csr_softmax mindspore.ops.sparse_add Gradient Clipping diff --git a/mindspore/python/mindspore/ops/function/sparse_func.py b/mindspore/python/mindspore/ops/function/sparse_func.py index f1d4b2f9bd6..83de78a5730 100644 --- a/mindspore/python/mindspore/ops/function/sparse_func.py +++ b/mindspore/python/mindspore/ops/function/sparse_func.py @@ -518,11 +518,12 @@ def csr_softmax(logits, dtype): dtype (dtype): Data type. Returns: - CSRTensor. a csr_tensor containing: - indptr: indicates the start and end point for `values` in each row. - indices: the column positions of all non-zero values of the input. - values: the non-zero values of the dense tensor. - shape: the shape of the csr_tensor. + CSRTensor, a csr_tensor containing + + - **indptr** - indicates the start and end point for `values` in each row. + - **indices** - the column positions of all non-zero values of the input. + - **values** - the non-zero values of the dense tensor. + - **shape** - the shape of the csr_tensor. Supported Platforms: ``GPU`` ``CPU`` @@ -531,19 +532,18 @@ def csr_softmax(logits, dtype): >>> import mindspore as ms >>> import mindspore.common.dtype as mstype >>> from mindspore import Tensor, CSRTensor - >>> from mindspore.ops.functional import sparse_matrix_softmax + >>> from mindspore.ops.function import csr_softmax >>> logits_indptr = Tensor([0, 4, 6], dtype=mstype.int32) >>> logits_indices = Tensor([0, 2, 3, 4, 3, 4], dtype=mstype.int32) >>> logits_values = Tensor([1, 2, 3, 4, 1, 2], dtype=mstype.float32) >>> shape = (2, 6) >>> logits = CSRTensor(logits_indptr, logits_indices, logits_values, shape) - >>> out = logits.sparse_matrix_softmax(dtype) + >>> out = csr_softmax(logits, dtype=mstype.float32) >>> print(out) - CSRTensor(shape=[2,6], dtype=Float32, - indptr=Tensor(shape=[3], dtype=Int64, value = [0, 4, 6]), - indices=Tensor(shape=[2], dtype=Int64, value = [0, 2, 3, 4, 3, 4]), - values=Tensor(shape=[2], dtype=Float32, - value = [3.2058e-02, 8.7144e-02, 2.3688e-01, 6.4391e-01, 2.6894e-01, 7.310e-01])) + CSRTensor(shape=[2, 6], dtype=Float32, indptr=Tensor(shape=[3], dtype=Int32, value=[0 4 6]), + indices=Tensor(shape=[6], dtype=Int32, value=[0 2 3 4 3 4]), + values=Tensor(shape=[6], dtype=Float32, value=[ 3.20586003e-02 8.71443152e-02 2.36882806e-01 + 6.43914223e-01 2.68941432e-01 7.31058598e-01])) """ if not isinstance(logits, CSRTensor): raise_type_error("For functional operator sparse_matrix_softmax, logits must be type of CSRTensor.") diff --git a/mindspore/python/mindspore/ops/operations/sparse_ops.py b/mindspore/python/mindspore/ops/operations/sparse_ops.py index fe2bff1cd21..46b8a592b4f 100644 --- a/mindspore/python/mindspore/ops/operations/sparse_ops.py +++ b/mindspore/python/mindspore/ops/operations/sparse_ops.py @@ -715,16 +715,25 @@ class SparseMatrixSoftmax(Primitive): """ Calculates the softmax of a CSRTensorMatrix. - Args: - logits (CSRTensor): Sparse CSR Tensor. - dtype (dtype): Data type. + .. warning:: + This is an experimental prototype that is subject to change and/or deletion. - Returns: - CSRTensor. a csr_tensor containing: - indptr: indicates the start and end point for `values` in each row. - indices: the column positions of all non-zero values of the input. - values: the non-zero values of the dense tensor. - shape: the shape of the csr_tensor. + Args: + dtype (dtype.Number) - The valid data type. Only constant value is allowed. + + Inputs: + - **x_dense_shape** (Tensor) - Input shape of the original Dense matrix. + - **x_batch_pointers** (Tensor) - The number of rows in the input matrix. + - **x_row_pointers** (Tensor) - Input the column coordinates of nonzero elements. + - **x_col_indices** (Tensor) - The number of input nonzero elements up to that line. + - **x_values** (Tensor) - The value of the input nonzero element. + + Outputs: + - **y_dense_shape** (Tensor) - Output shape of the original Dense matrix. + - **y_batch_pointers** (Tensor) - The number of rows in the output matrix. + - **y_row_pointers** (Tensor) - Output the column coordinates of nonzero elements. + - **y_col_indices** (Tensor) - The number of output nonzero elements up to that line. + - **y_values** (Tensor) - The value of the input nonzero element. Supported Platforms: ``GPU`` ``CPU`` @@ -733,21 +742,27 @@ class SparseMatrixSoftmax(Primitive): >>> import mindspore as ms >>> import mindspore.common.dtype as mstype >>> from mindspore import Tensor, CSRTensor - >>> from mindspore.ops.functional import sparse_matrix_softmax + >>> from mindspore.ops.operations.sparse_ops import SparseMatrixSoftmax >>> logits_indptr = Tensor([0, 4, 6], dtype=mstype.int32) >>> logits_indices = Tensor([0, 2, 3, 4, 3, 4], dtype=mstype.int32) >>> logits_values = Tensor([1, 2, 3, 4, 1, 2], dtype=mstype.float32) >>> shape = (2, 6) >>> logits = CSRTensor(logits_indptr, logits_indices, logits_values, shape) - >>> out = logits.sparse_matrix_softmax(dtype) + >>> net = SparseMatrixSoftmax(mstype.float32) + >>> logits_pointers =Tensor(logits.values.shape[0], mstype.int32) + >>> out = net(Tensor(logits.shape, dtype=mstype.int32), logits_pointers, + ... logits.indptr, logits.indices, logits.values) >>> print(out) - CSRTensor(shape=[2,6], dtype=Float32, - indptr=Tensor(shape=[3], dtype=Int64, value = [0, 4, 6]), - indices=Tensor(shape=[2], dtype=Int64, value = [0, 2, 3, 4, 3, 4]), - values=Tensor(shape=[2], dtype=Float32, - value = [3.2058e-02, 8.7144e-02, 2.3688e-01, 6.4391e-01, 2.6894e-01, 7.310e-01])) + (Tensor(shape=[2], dtype=Int32, value= [2, 6]), + Tensor(shape=[], dtype=Int32, value= 6), + Tensor(shape=[3], dtype=Int32, value= [0, 4, 6]), + Tensor(shape=[6], dtype=Int32, value= [0, 2, 3, 4, 3, 4]), + Tensor(shape=[6], dtype=Float32, value= [ 3.20586003e-02, 8.71443152e-02, + 2.36882806e-01, 6.43914223e-01, 2.68941432e-01, 7.31058598e-01])) """ + + @prim_attr_register def __init__(self, dtype): '''Initialize for SparseMatrixSoftmax'''