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1# Copyright 2022 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"""smoke tests for RowTensor operations"""
16
17import pytest
18import numpy as np
19
20from mindspore import Tensor, nn, context
21from mindspore.common.sparse_tensor import RowTensorInner
22from mindspore.common import dtype as mstype
23
24
25def compare_row(row1, row2):
26    assert isinstance(row1, RowTensorInner)
27    assert isinstance(row2, RowTensorInner)
28    assert (row1.indices.asnumpy() == row1.indices.asnumpy()).all()
29    assert (row2.values.asnumpy() == row2.values.asnumpy()).all()
30    assert row1.dense_shape == row2.dense_shape
31
32
33@pytest.mark.level2
34@pytest.mark.platform_arm_ascend_training
35@pytest.mark.platform_x86_ascend_training
36@pytest.mark.platform_x86_gpu_training
37@pytest.mark.platform_x86_cpu
38@pytest.mark.env_onecard
39def test_make_row():
40    """
41    Feature: Test RowTensor Constructor in Graph and PyNative.
42    Description: Test RowTensorInner(indices, values, shape) and RowTensorInner(RowTensor)
43    Expectation: Success.
44    """
45    indices = Tensor([0, 1], dtype=mstype.int32)
46    values = Tensor([[1, 2], [3, 4]], dtype=mstype.float32)
47    dense_shape = (3, 2)
48
49    def test_pynative():
50        return RowTensorInner(indices, values, dense_shape)
51
52    row1 = test_pynative()
53    compare_row(row1, row1)
54    row2 = RowTensorInner(row_tensor=row1)
55    compare_row(row1, row2)
56
57
58@pytest.mark.level2
59@pytest.mark.platform_arm_ascend_training
60@pytest.mark.platform_x86_ascend_training
61@pytest.mark.platform_x86_gpu_training
62@pytest.mark.env_onecard
63def test_row_tensor_with_control_if():
64    """
65    Feature: Test RowTensor in if.
66    Description: Test RowTensor computation in while loop.
67    Expectation: Success.
68    """
69    class RowTensorValuesDouble(nn.Cell):
70
71        def construct(self, x):
72            indices = x.indices
73            values = x.values * 2
74            shape = x.dense_shape
75            return RowTensorInner(indices, values, shape)
76
77    class RowTensorValuesAdd2(nn.Cell):
78
79        def construct(self, x):
80            indices = x.indices
81            values = x.values + 2
82            shape = x.dense_shape
83            return RowTensorInner(indices, values, shape)
84
85    class RowTensorWithControlIf(nn.Cell):
86        def __init__(self, shape):
87            super(RowTensorWithControlIf, self).__init__()
88            self.op1 = RowTensorValuesDouble()
89            self.op2 = RowTensorValuesAdd2()
90            self.shape = shape
91
92        def construct(self, a, b, indices, values):
93            x = RowTensorInner(indices, values, self.shape)
94            if a > b:
95                x = self.op1(x)
96            else:
97                x = self.op2(x)
98            return x.indices, x.values, x.dense_shape
99    context.set_context(mode=context.PYNATIVE_MODE)
100    a = Tensor(0, mstype.int32)
101    b = Tensor(2, mstype.int32)
102    indices = Tensor([0, 1], dtype=mstype.int32)
103    values = Tensor([[1, 2], [3, 4]], dtype=mstype.float32)
104    shape = (3, 2)
105    net = RowTensorWithControlIf(shape)
106    out = net(a, b, indices, values)
107    assert np.allclose(out[0].asnumpy(), indices.asnumpy(), .0, .0)
108    assert np.allclose(out[1].asnumpy(), values.asnumpy() + 2, .0, .0)
109    assert out[2] == shape
110