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100 lines
2.9 KiB
100 lines
2.9 KiB
# Copyright 2019-2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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from mindspore.common.api import ms_function
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from mindspore.common.initializer import initializer
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from mindspore.common.parameter import Parameter
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from mindspore.common.tensor import Tensor
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from mindspore.nn import Cell
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from mindspore.ops.operations import Tile
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class TileNet(Cell):
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def __init__(self, numpy_input):
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super(TileNet, self).__init__()
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self.Tile = Tile()
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self.input_parameter = Parameter(initializer(Tensor(numpy_input), numpy_input.shape), name='x')
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@ms_function
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def construct(self, mul):
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return self.Tile(self.input_parameter, mul)
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def ms_tile(nptype):
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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input_0 = np.arange(2).reshape((2, 1, 1)).astype(nptype)
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mul_0 = (8, 1, 1)
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input_1 = np.arange(32).reshape((2, 4, 4)).astype(nptype)
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mul_1 = (2, 2, 2)
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input_2 = np.arange(1).reshape((1, 1, 1)).astype(nptype)
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mul_2 = (1, 1, 1)
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tile_net = TileNet(input_0)
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np_expected = np.tile(input_0, mul_0)
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ms_output = tile_net(mul_0).asnumpy()
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np.testing.assert_array_equal(ms_output, np_expected)
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tile_net = TileNet(input_1)
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np_expected = np.tile(input_1, mul_1)
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ms_output = tile_net(mul_1).asnumpy()
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np.testing.assert_array_equal(ms_output, np_expected)
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tile_net = TileNet(input_2)
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np_expected = np.tile(input_2, mul_2)
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ms_output = tile_net(mul_2).asnumpy()
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np.testing.assert_array_equal(ms_output, np_expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_float16():
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ms_tile(np.float16)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_float32():
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ms_tile(np.float32)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_float64():
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ms_tile(np.float64)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_int16():
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ms_tile(np.int16)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_int32():
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ms_tile(np.int32)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_int64():
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ms_tile(np.int64)
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