|
- # coding: utf-8
-
- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
-
- # limitations under the License.
- # ============================================================================
-
- """Operators for sparse operators."""
-
- from ..._checkparam import Validator as validator
- from ...common import dtype as mstype
- from ..primitive import PrimitiveWithInfer, prim_attr_register
-
- class SparseToDense(PrimitiveWithInfer):
- """
- Convert a sparse representation into a dense tensor.
-
- Inputs:
- - **indices** (Tensor) - The indices of sparse representation.
- - **values** (Tensor) - Values corresponding to each row of indices.
- - **dense_shape** (tuple) - An int tuple which specifies the shape of dense tensor.
-
- Returns:
- Tensor, the shape of tensor is `dense_shape`.
-
- Examples:
- >>> indices = Tensor([[0, 1], [1, 2]])
- >>> values = Tensor([1, 2], dtype=ms.float32)
- >>> dense_shape = (3, 4)
- >>> out = P.SparseToDense()(indices, values, dense_shape)
- """
-
- @prim_attr_register
- def __init__(self):
- """init index_select"""
- self.init_prim_io_names(inputs=['indices', 'values', 'dense_shape'], outputs=['output'])
-
- def __infer__(self, indices, values, dense_shape):
- validator.check_subclass("indices", indices['dtype'], mstype.tensor, self.name)
- validator.check_subclass("values", values['dtype'], mstype.tensor, self.name)
- out = {'shape': dense_shape['value'],
- 'dtype': values['dtype'],
- 'value': None}
- return out
|
