forked from mindspore-Ecosystem/mindspore
51 lines
1.9 KiB
Python
51 lines
1.9 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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from mindspore import jit
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from mindspore import Tensor, export, load, Parameter, dtype, context
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from mindspore.nn import GraphCell
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def test_controller():
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"""
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Feature: Test MindIR Export msfunction without using decorator.
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Description: test msfunction export as mindir.
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Expectation: No exception, assert True.
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"""
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def controller(x, y):
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w = Parameter(Tensor([-2], dtype.float32), name="weight")
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b = Parameter(Tensor([-5], dtype.float32), name="bias")
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if len(x.shape) == 1:
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return y
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while y >= x:
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if b <= x:
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return y
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if w < x:
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return x
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x += y
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return x + y
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context.set_context(mode=context.GRAPH_MODE)
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input1 = Tensor(np.array([3], np.float32))
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input2 = Tensor(np.array([0], np.float32))
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controller_graph = jit(fn=controller)
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expected_out = controller_graph(input1, input2)
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export(controller_graph, input1, input2, file_name="control.mindir", file_format="MINDIR")
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c_graph = load("control.mindir")
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c_net = GraphCell(c_graph)
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actual_out = c_net(input1, input2)
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assert np.allclose(actual_out.asnumpy(), expected_out.asnumpy())
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