forked from huawei/mindspore2022
39 lines
1.7 KiB
Python
39 lines
1.7 KiB
Python
# 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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Layer.
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The high-level components(Cells) used to construct the neural network.
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"""
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from .activation import Softmax, LogSoftmax, ReLU, ReLU6, Tanh, GELU, ELU, Sigmoid, PReLU, get_activation, LeakyReLU, HSigmoid, HSwish
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from .normalization import BatchNorm1d, BatchNorm2d, LayerNorm
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from .container import SequentialCell, CellList
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from .conv import Conv2d, Conv2dTranspose
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from .lstm import LSTM
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from .basic import Dropout, Flatten, Dense, ClipByNorm, Norm, OneHot, ImageGradients, Pad
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from .embedding import Embedding
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from .pooling import AvgPool2d, MaxPool2d
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__all__ = ['Softmax', 'LogSoftmax', 'ReLU', 'ReLU6', 'Tanh', 'GELU', 'Sigmoid',
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'PReLU', 'get_activation', 'LeakyReLU', 'HSigmoid', 'HSwish', 'ELU',
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'BatchNorm1d', 'BatchNorm2d', 'LayerNorm',
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'SequentialCell', 'CellList',
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'Conv2d', 'Conv2dTranspose',
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'LSTM',
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'Dropout', 'Flatten', 'Dense', 'ClipByNorm', 'Norm', 'OneHot', 'ImageGradients',
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'Embedding',
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'AvgPool2d', 'MaxPool2d', 'Pad',
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]
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