mindspore/tests/ut/python/mindir/test_mindir_export.py

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# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
import numpy as np
from mindspore.nn import Cell, GraphCell
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from mindspore import ops
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from mindspore import Tensor, export, load, Parameter, dtype, context
def test_export_control_flow():
"""
Feature: Test MindIR Export model
Description: test mindir export when parameter is not use
Expectation: No exception.
"""
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class Net(Cell):
def __init__(self):
super(Net, self).__init__()
self.w = Parameter(Tensor([-2], dtype.float32), name="weight")
self.b = Parameter(Tensor([-5], dtype.float32), name="bias")
def construct(self, x, y):
if len(x.shape) == 1:
return y
while y >= x:
if self.b <= x:
return y
elif self.w < x:
return x
x += y
return x + y
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context.set_context(mode=context.GRAPH_MODE)
x = np.array([3], np.float32)
y = np.array([0], np.float32)
net = Net()
export(net, Tensor(x), Tensor(y), file_name="ctrl", file_format='MINDIR')
graph = load('ctrl.mindir')
g_net = GraphCell(graph)
export_out = g_net(Tensor(x), Tensor(y))
correct_out = net(Tensor(x), Tensor(y))
assert np.allclose(export_out.asnumpy(), correct_out.asnumpy())
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def test_mindir_export_none():
"""
Feature: Test MindIR Export model
Description: test mindir export type none
Expectation: No exception.
"""
class TestCell(Cell):
def __init__(self):
super(TestCell, self).__init__()
self.relu = ops.ReLU()
def construct(self, x):
return self.relu(x), None, None
input_tensor = Tensor(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]))
net = TestCell()
export(net, input_tensor, file_name="none_net", file_format='MINDIR')
graph = load("none_net.mindir")
assert graph is not None