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95 lines
3.0 KiB
95 lines
3.0 KiB
# Copyright 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 import Tensor
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from mindspore.nn import Cell
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import mindspore.ops as P
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
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class SqueezeNet(Cell):
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def __init__(self):
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super(SqueezeNet, self).__init__()
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self.squeeze = P.Squeeze()
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def construct(self, x):
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return self.squeeze(x)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_squeeze_shape_float32():
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x = np.ones(shape=[1, 2, 1, 1, 8, 3, 1]).astype(np.float32)
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expect = np.ones(shape=[2, 8, 3]).astype(np.float32)
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net = SqueezeNet()
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result = net(Tensor(x))
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assert np.allclose(result.asnumpy(), expect, rtol=1.e-4,
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atol=1.e-8, equal_nan=True)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_squeeze_shape_int32():
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x = np.array([[7], [11]]).astype(np.int32)
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expect = np.array([7, 11]).astype(np.int32)
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net = SqueezeNet()
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result = net(Tensor(x))
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assert np.allclose(result.asnumpy(), expect, rtol=1.e-4,
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atol=1.e-8, equal_nan=True)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_squeeze_shape_bool():
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x = np.array([[True], [False]]).astype(np.bool_)
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expect = np.array([True, False]).astype(np.bool_)
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net = SqueezeNet()
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result = net(Tensor(x))
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assert np.allclose(result.asnumpy(), expect, rtol=1.e-4,
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atol=1.e-8, equal_nan=True)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_squeeze_shape_float64():
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x = np.random.random([1, 2, 1, 1, 8, 3, 1]).astype(np.float64)
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expect = np.squeeze(x)
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net = SqueezeNet()
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result = net(Tensor(x))
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print(result.asnumpy()[0][0], expect[0][0])
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assert np.allclose(result.asnumpy(), expect, rtol=1.e-4,
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atol=1.e-8, equal_nan=True)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_squeeze_shape_uint16():
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x = np.random.random([1, 2, 1, 1, 8, 3, 1]).astype(np.uint16)
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expect = np.squeeze(x)
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net = SqueezeNet()
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result = net(Tensor(x))
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print(result.asnumpy()[0][0], expect[0][0])
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assert np.allclose(result.asnumpy(), expect, rtol=1.e-4,
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atol=1.e-8, equal_nan=True)
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