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109 lines
2.7 KiB
109 lines
2.7 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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"""
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test nn.Triu()
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"""
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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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def test_triu():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.value = Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
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def construct(self):
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triu = nn.Triu()
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return triu(self.value, 0)
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net = Net()
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out = net()
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assert np.sum(out.asnumpy()) == 26
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def test_triu_1():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.value = Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
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def construct(self):
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triu = nn.Triu()
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return triu(self.value, 1)
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net = Net()
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out = net()
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assert np.sum(out.asnumpy()) == 11
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def test_triu_2():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.value = Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
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def construct(self):
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triu = nn.Triu()
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return triu(self.value, -1)
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net = Net()
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out = net()
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assert np.sum(out.asnumpy()) == 38
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def test_triu_parameter():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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def construct(self, x):
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triu = nn.Triu()
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return triu(x, 0)
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net = Net()
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net(Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
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def test_triu_parameter_1():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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def construct(self, x):
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triu = nn.Triu()
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return triu(x, 1)
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net = Net()
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net(Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
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def test_triu_parameter_2():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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def construct(self, x):
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triu = nn.Triu()
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return triu(x, -1)
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net = Net()
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net(Tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
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