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- # Copyright 2021 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.
- # ============================================================================
- """ test syntax for logic expression """
-
- import numpy as np
-
- import mindspore.nn as nn
- import mindspore
- from mindspore import context
- from mindspore.common.tensor import Tensor
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE)
-
-
- class ArgumentNum(nn.Cell):
- def __init__(self):
- super().__init__()
- self.matmul = P.MatMul()
-
- def construct(self, x, y):
- super(ArgumentNum, 2, 3).aa()
- out = self.matmul(x, y)
- return out
-
-
- def test_super_argument_num():
- x = Tensor(np.ones(shape=[1, 3]), mindspore.float32)
- y = Tensor(np.ones(shape=[3, 4]), mindspore.float32)
- net = ArgumentNum()
- ret = net(x, y)
- print(ret)
-
-
- class ArgumentNotSelf(nn.Cell):
- def __init__(self):
- super().__init__()
- self.matmul = P.MatMul()
-
- def construct(self, x, y):
- super(ArgumentNotSelf, 2).aa()
- out = self.matmul(x, y)
- return out
-
-
- def test_super_argument_not_self():
- x = Tensor(np.ones(shape=[1, 3]), mindspore.float32)
- y = Tensor(np.ones(shape=[3, 4]), mindspore.float32)
- net = ArgumentNotSelf()
- ret = net(x, y)
- print(ret)
-
-
- class ArgumentType(nn.Cell):
- def __init__(self):
- super().__init__()
- self.matmul = P.MatMul()
-
- def construct(self, x, y):
- super(ArgumentType, self).aa()
- out = self.matmul(x, y)
- return out
-
-
- def test_super_argument_type():
- x = Tensor(np.ones(shape=[1, 3]), mindspore.float32)
- y = Tensor(np.ones(shape=[3, 4]), mindspore.float32)
- net = ArgumentType()
- ret = net(x, y)
- print(ret)
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