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@@ -1,4 +1,4 @@ |
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# Copyright 2020 Huawei Technologies Co., Ltd |
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# Copyright 2020-2021 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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@@ -21,7 +21,6 @@ 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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class Net(nn.Cell): |
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def __init__(self): |
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super(Net, self).__init__() |
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@@ -31,20 +30,32 @@ class Net(nn.Cell): |
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return self.select(cond_op, input_x, input_y) |
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cond = np.array([[True, False], [True, False]]).astype(np.bool) |
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x = np.array([[1.2, 1], [1, 0]]).astype(np.float32) |
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y = np.array([[1, 2], [3, 4.0]]).astype(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_select(): |
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU") |
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select = Net() |
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cond = np.array([[True, False], [True, False]]).astype(np.bool) |
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x = np.array([[1.2, 1], [1, 0]]).astype(np.float32) |
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y = np.array([[1, 2], [3, 4.0]]).astype(np.float32) |
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output = select(Tensor(cond), Tensor(x), Tensor(y)) |
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expect = [[1.2, 2], [1, 4.0]] |
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error = np.ones(shape=[2, 2]) * 1.0e-6 |
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diff = output.asnumpy() - expect |
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assert np.all(diff < error) |
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assert np.all(-diff < error) |
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU") |
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x = np.array([[1, 0], [1, 0]]).astype(np.bool) |
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y = np.array([[0, 0], [1, 1]]).astype(np.bool) |
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output = select(Tensor(cond), Tensor(x), Tensor(y)) |
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expect = np.array([[1, 0], [1, 1]]).astype(np.bool) |
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assert np.all(output.asnumpy() == expect) |
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") |
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x = np.array([[1, 0], [1, 0]]).astype(np.bool) |
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y = np.array([[0, 0], [1, 1]]).astype(np.bool) |
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output = select(Tensor(cond), Tensor(x), Tensor(y)) |
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expect = np.array([[1, 0], [1, 1]]).astype(np.bool) |
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assert np.all(output.asnumpy() == expect) |