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102 lines
2.7 KiB
102 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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""" Test L1Regularizer """
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import math
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import numpy as np
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import mindspore.nn as nn
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import mindspore.context as context
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from mindspore import Tensor, ms_function
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context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
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class Net_l1_regularizer(nn.Cell):
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def __init__(self, scale):
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super(Net_l1_regularizer, self).__init__()
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self.l1_regularizer = nn.L1Regularizer(scale)
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@ms_function
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def construct(self, weights):
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return self.l1_regularizer(weights)
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def test_l1_regularizer02():
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scale = 0.0
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weights = Tensor(np.array([[1.0, -2.0], [-3.0, 4.0]]).astype(np.float32))
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer(weights)
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except ValueError:
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assert True
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def test_l1_regularizer03():
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scale = -0.5
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weights = Tensor(np.array([[1.0, -2.0], [-3.0, 4.0]]).astype(np.float32))
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer(weights)
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except ValueError:
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assert True
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def test_l1_regularizer04():
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scale = math.inf
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weights = Tensor(np.array([[1.0, -2.0], [-3.0, 4.0]]).astype(np.float32))
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer(weights)
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except ValueError:
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assert True
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def test_l1_regularizer05():
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scale = math.nan
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weights = Tensor(np.array([[1.0, -2.0], [-3.0, 4.0]]).astype(np.float32))
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer(weights)
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except ValueError:
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assert True
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def test_l1_regularizer06():
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scale = 0.5
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weights = "sss"
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer(weights)
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except TypeError:
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assert True
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def test_l1_regularizer07():
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scale = 0.5
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try:
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l1_regularizer = Net_l1_regularizer(scale)
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l1_regularizer()
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except TypeError:
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assert True
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def test_l1_regularizer09():
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scale = 0.5
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weights = Tensor([[False, False], [False, False]])
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try:
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net = nn.L1Regularizer(scale)
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net(weights)
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except TypeError:
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assert True
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