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1# Copyright 2020 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15"""
16@File  : test_sparse_tensor.py
17@Author:
18@Date  : 2020-07-16
19@Desc  : test mindspore sparse_tensor's operation
20"""
21import numpy as np
22import pytest
23
24import mindspore as ms
25import mindspore.nn as nn
26from mindspore.ops import composite as C
27from mindspore import Tensor, SparseTensor, context
28
29@pytest.fixture(scope="module", autouse=True)
30def setup_teardown():
31    context.set_context(mode=context.GRAPH_MODE, enable_sparse=True)
32    yield
33    context.set_context(enable_sparse=False)
34
35
36grad_op = C.GradOperation(get_all=True)
37
38class MakeSparseTensor(nn.Cell):
39    def __init__(self, dense_shape):
40        super(MakeSparseTensor, self).__init__()
41        self.dense_shape = dense_shape
42    def construct(self, indices, values):
43        ret = (SparseTensor(indices, values, self.dense_shape),)
44        return ret[0]
45
46
47def test_sparse_tensor_make_sparse_tensor():
48    indices = Tensor([[0, 1], [1, 2]])
49    values = Tensor([1, 2], dtype=ms.float32)
50    MakeSparseTensor((3, 4))(indices, values)
51
52
53def test_sparse_tensor_attr():
54    class SparseTensorGetAttr(nn.Cell):
55        def __init__(self):
56            super(SparseTensorGetAttr, self).__init__()
57            self.dense_shape = (3, 4)
58        def construct(self, indices, values):
59            x = SparseTensor(indices, values, self.dense_shape)
60            return x.values, x.indices, x.dense_shape
61
62    indices = Tensor([[0, 1], [1, 2]])
63    values = Tensor([1, 2], dtype=ms.float32)
64    SparseTensorGetAttr()(indices, values)
65    grad_op(SparseTensorGetAttr())(indices, values)
66
67
68def test_sparse_tensor_indices_dim_greater_than_dense_shape_dim():
69    indices = Tensor(np.array([[0, 0, 0], [0, 0, 1]], dtype=np.int32))
70    values = Tensor(np.array([100, 200], dtype=np.float32))
71    dense_shape = (2, 2)
72    with pytest.raises(TypeError):
73        MakeSparseTensor(dense_shape)(indices, values)
74
75
76def test_sparse_tensor_indices_dim_less_than_dense_shape_dim():
77    indices = Tensor(np.array([[0, 0], [0, 1]], dtype=np.int32))
78    values = Tensor(np.array([100, 200], dtype=np.float32))
79    dense_shape = (2, 2, 2)
80    with pytest.raises(TypeError):
81        MakeSparseTensor(dense_shape)(indices, values)
82
83
84def test_sparse_tensor_to_tensor():
85    class SparseToDenseCell(nn.Cell):
86        def __init__(self, dense_shape):
87            super(SparseToDenseCell, self).__init__()
88            self.dense_shape = dense_shape
89            self.sparse_to_dense = nn.SparseToDense()
90        def construct(self, indices, values):
91            sparse = SparseTensor(indices, values, self.dense_shape)
92            return self.sparse_to_dense(sparse)
93
94    indices = Tensor([[0, 1], [1, 2]])
95    values = Tensor([1, 2], dtype=ms.float32)
96    dense_shape = (3, 4)
97    SparseToDenseCell(dense_shape)(indices, values)
98    grad_op(SparseToDenseCell(dense_shape))(indices, values)
99