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