forked from mindspore-Ecosystem/mindspore
144 lines
4.5 KiB
Python
144 lines
4.5 KiB
Python
# Copyright 2022 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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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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class MaskedFillNet(nn.Cell):
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def __init__(self):
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super(MaskedFillNet, self).__init__()
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self.maskedfill = P.MaskedFill()
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def construct(self, inputs, mask, value):
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return self.maskedfill(inputs, mask, value)
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def maskedfill_fun(ntype):
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maskedfill_net = MaskedFillNet()
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inputs = Tensor(np.array([[1, 2, 3, 4], [5, 6, 7, 8]]).astype(ntype))
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mask = Tensor(np.array([[True, True, False, True], [False, False, True, False]]).astype(np.bool))
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value = Tensor(np.array(22).astype(ntype))
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expect = np.array([[22, 22, 3, 22], [5, 6, 22, 8]]).astype(ntype)
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output = maskedfill_net(inputs, mask, value)
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assert (output.asnumpy() == expect).all()
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mask = Tensor(np.array([[True, True, True, True], [True, True, True, True]]).astype(np.bool))
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value = Tensor(np.array(1).astype(ntype))
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expect = np.array([[1, 1, 1, 1], [1, 1, 1, 1]]).astype(ntype)
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output = maskedfill_net(inputs, mask, value)
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assert (output.asnumpy() == expect).all()
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mask = Tensor(np.array([[False, False, False, False], [False, False, False, False]]).astype(np.bool))
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value = Tensor(np.array(22).astype(ntype))
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expect = np.array([[1, 2, 3, 4], [5, 6, 7, 8]]).astype(ntype)
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output = maskedfill_net(inputs, mask, value)
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assert (output.asnumpy() == expect).all()
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# BroadCast
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mask = Tensor(np.array([True, True, False, True]).astype(np.bool))
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value = Tensor(np.array(22).astype(ntype))
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expect = np.array([[22, 22, 3, 22], [22, 22, 7, 22]]).astype(ntype)
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output = maskedfill_net(inputs, mask, value)
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assert (output.asnumpy() == expect).all()
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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_maskedfill_float():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with float input.
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Expectation: The result match to expect.
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"""
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maskedfill_fun(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_maskedfill_float16():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with float16 input.
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Expectation: The result match to expect.
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"""
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maskedfill_fun(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_maskedfill_int():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with int input.
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Expectation: The result match to expect.
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"""
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maskedfill_fun(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_maskedfill_int8():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with int8 input.
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Expectation: The result match to expect.
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"""
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maskedfill_fun(np.int8)
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def maskedfill_value(value):
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maskedfill_net = MaskedFillNet()
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inputs = Tensor(np.array([1, 2, 3, 4]).astype(np.float32))
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mask = Tensor(np.array([True, True, False, True]).astype(np.bool))
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expect = np.array([0.5, 0.5, 3, 0.5]).astype(np.float32)
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output = maskedfill_net(inputs, mask, value)
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assert (output.asnumpy() == expect).all()
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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_maskedfill_float_value():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with float value.
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Expectation: The result match to expect.
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"""
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maskedfill_value(0.5)
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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_maskedfill_tensor_value():
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"""
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Feature: Test MaskedFill op.
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Description: Test MaskedFill with tensor input.
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Expectation: The result match to expect.
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"""
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maskedfill_value(Tensor(0.5))
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