forked from mindspore-Ecosystem/mindspore
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
# Copyright 2020 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 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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from mindspore.common import dtype as mstype
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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class Net(nn.Cell):
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def __init__(self, shape, seed=0, seed2=0):
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super(Net, self).__init__()
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self.uniformint = P.UniformInt(seed=seed)
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self.shape = shape
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def construct(self, a, b):
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return self.uniformint(self.shape, a, b)
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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_net_1D():
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seed = 10
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shape = (3, 2, 4)
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a = 1
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b = 5
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net = Net(shape, seed=seed)
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ta, tb = Tensor(a, mstype.int32), Tensor(b, mstype.int32)
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output = net(ta, tb)
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assert output.shape == (3, 2, 4)
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