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!17739 Sparse API modification 

From: @wanyiming
Reviewed-by: @kingxian,@zh_qh
Signed-off-by: @kingxian,@zh_qh
This commit is contained in:
mindspore-ci-bot 2021-06-08 09:52:31 +08:00 committed by Gitee
parent 88f5c60264 819bd8c463
commit 2ec087e5bd
1 changed files with 10 additions and 10 deletions
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20
mindspore/nn/sparse/sparse.py
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@ -24,7 +24,7 @@ class SparseToDense(Cell):
Not yet supported by any backend at the moment.
Inputs:
- **sparse_tensor** (SparseTensor): the sparse tensor to convert.
- **sparse_tensor** (:class:`mindspore.SparseTensor`): the sparse tensor to convert.
Outputs:
Tensor, converted from sparse tensor.
@ -69,21 +69,21 @@ class SparseTensorDenseMatmul(Cell):
The rank of sparse matrix and dense matrix must equal to `2`.
Args:
- *adjoint_st** (bool) - If true, sparse tensor is transposed before multiplication. Default: False.
- *adjoint_dt** (bool) - If true, dense tensor is transposed before multiplication. Default: False.
adjoint_st (bool): If true, sparse tensor is transposed before multiplication. Default: False.
adjoint_dt (bool): If true, dense tensor is transposed before multiplication. Default: False.
Inputs:
- **indices** (Tensor) - A 2-D Tensor, represents the position of the element in the sparse tensor.
Support int32, int64, each element value should be non-negative. The shape is :math:`(n, 2)`.
Support int32, int64, each element value should be non-negative. The shape is :math:`(n, 2)`.
- **values** (Tensor) - A 1-D Tensor, represents the value corresponding to the position in the `indices`.
Support float16, float32, float64, int32, int64. The shape should be :math:`(n,).
Support float16, float32, float64, int32, int64. The shape should be :math:`(n,)`.
- **sparse_shape** (tuple) - A positive int tuple which specifies the shape of sparse tensor,
should have 2 elements, represent sparse tensor shape is :math:`(N, C)`.
should have 2 elements, represent sparse tensor shape is :math:`(N, C)`.
- **dense** (Tensor) - A 2-D Tensor, the dtype is same as `values`.
If `adjoint_st` is False and `adjoint_dt` is False, the shape must be :math:`(C, M)`.
If `adjoint_st` is False and `adjoint_dt` is True, the shape must be :math:`(M, C)`.
If `adjoint_st` is True and `adjoint_dt` is False, the shape must be :math:`(N, M)`.
If `adjoint_st` is True and `adjoint_dt` is True, the shape must be :math:`(M, N)`.
If `adjoint_st` is False and `adjoint_dt` is False, the shape must be :math:`(C, M)`.
If `adjoint_st` is False and `adjoint_dt` is True, the shape must be :math:`(M, C)`.
If `adjoint_st` is True and `adjoint_dt` is False, the shape must be :math:`(N, M)`.
If `adjoint_st` is True and `adjoint_dt` is True, the shape must be :math:`(M, N)`.
Outputs:
Tensor, the dtype is the same as `values`.