forked from mindspore-Ecosystem/mindspore
Add testcase for control flow with monad.
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# 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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import numpy as np
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import pytest
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import mindspore
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from mindspore import context, nn, ops, Tensor, Parameter
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class Net(nn.Cell):
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def __init__(self):
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super().__init__()
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self.print = ops.Print()
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self.param_a = Parameter(Tensor(5, mindspore.int32), name='a')
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self.param_b = Parameter(Tensor(4, mindspore.int32), name='b')
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def construct(self, x):
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out = 0
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for _ in range(2):
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out += self.func1(x)
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return out
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def func1(self, x):
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out = x
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i = 0
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while i < 1:
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out += self.func2(x)
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i = i + 1
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self.print(out)
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return out
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def func2(self, x):
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if x > 10:
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return self.param_a
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return self.param_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_repeat_control_arrow_for_stack_actor():
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"""
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Feature: Runtime.
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Description: Duplicate side effects depend on stack actors..
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Expectation: No exception.
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = Tensor(np.array([1]), mindspore.int32)
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net = Net()
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out = net(x)
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result = 10
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assert out == result
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