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142 lines
4.0 KiB
142 lines
4.0 KiB
# 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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""" test super"""
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import numpy as np
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore import context
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context.set_context(mode=context.GRAPH_MODE)
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class FatherNet(nn.Cell):
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def __init__(self, x):
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super(FatherNet, self).__init__(x)
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self.x = x
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def construct(self, x, y):
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return self.x * x
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def test_father(self, x):
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return self.x + x
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class MatherNet(nn.Cell):
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def __init__(self, y):
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super(MatherNet, self).__init__()
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self.y = y
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def construct(self, x, y):
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return self.y * y
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def test_mather(self, y):
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return self.y + y
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class SingleSubNet(FatherNet):
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def __init__(self, x, z):
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super(SingleSubNet, self).__init__(x)
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self.z = z
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def construct(self, x, y):
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ret_father_construct = super().construct(x, y)
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ret_father_test = super(SingleSubNet, self).test_father(x)
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ret_father_x = super(SingleSubNet, self).x
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ret_sub_z = self.z
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return ret_father_construct, ret_father_test, ret_father_x, ret_sub_z
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class MulSubNet(FatherNet, MatherNet):
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def __init__(self, x, y, z):
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super(MulSubNet, self).__init__(x)
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super(FatherNet, self).__init__(y)
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self.z = z
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def construct(self, x, y):
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ret_father_construct = super().construct(x, y)
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ret_father_test = super(MulSubNet, self).test_father(x)
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ret_father_x = super(MulSubNet, self).x
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ret_mather_construct = super(FatherNet, self).construct(x, y)
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ret_mather_test = super(FatherNet, self).test_mather(y)
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ret_mather_y = super(FatherNet, self).y
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ret_sub_z = self.z
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return ret_father_construct, ret_father_test, ret_father_x, \
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ret_mather_construct, ret_mather_test, ret_mather_y, ret_sub_z
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class Net(nn.Cell):
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def __init__(self, x):
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super(Net, self).__init__()
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self.x = x
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def construct(self, x, y):
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ret = super(Net, self).construct(x, y)
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return ret
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def test_single_super():
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single_net = SingleSubNet(2, 3)
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x = Tensor(np.ones([1, 2, 3], np.int32))
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y = Tensor(np.ones([1, 2, 3], np.int32))
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single_net(x, y)
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def test_mul_super():
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mul_net = MulSubNet(2, 3, 4)
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x = Tensor(np.ones([1, 2, 3], np.int32))
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y = Tensor(np.ones([1, 2, 3], np.int32))
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mul_net(x, y)
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def test_super_cell():
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net = Net(2)
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x = Tensor(np.ones([1, 2, 3], np.int32))
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y = Tensor(np.ones([1, 2, 3], np.int32))
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assert net(x, y) is None
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def test_single_super_in():
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class FatherNetIn(nn.Cell):
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def __init__(self, x):
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super(FatherNetIn, self).__init__(x)
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self.x = x
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def construct(self, x, y):
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return self.x * x
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def test_father(self, x):
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return self.x + x
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class SingleSubNetIN(FatherNetIn):
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def __init__(self, x, z):
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super(SingleSubNetIN, self).__init__(x)
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self.z = z
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def construct(self, x, y):
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ret_father_construct = super().construct(x, y)
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ret_father_test = super(SingleSubNetIN, self).test_father(x)
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ret_father_x = super(SingleSubNetIN, self).x
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ret_sub_z = self.z
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return ret_father_construct, ret_father_test, ret_father_x, ret_sub_z
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single_net_in = SingleSubNetIN(2, 3)
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x = Tensor(np.ones([1, 2, 3], np.int32))
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y = Tensor(np.ones([1, 2, 3], np.int32))
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single_net_in(x, y)
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