# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # 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. # TODO: define activation functions of neural network from . import rnn # noqa: F401 from . import transformer # noqa: F401 from . import container # noqa: F401 from .activation import CELU # noqa: F401 from .activation import PReLU # noqa: F401 from .activation import ReLU # noqa: F401 from .activation import ReLU6 # noqa: F401 from .activation import LeakyReLU # noqa: F401 from .activation import Sigmoid # noqa: F401 from .activation import Softmax # noqa: F401 from .activation import LogSoftmax # noqa: F401 from .activation import RReLU # noqa: F401 from .activation import Softmax2D # noqa: F401 from .common import Bilinear # noqa: F401 from .common import Pad1D # noqa: F401 from .common import Pad2D # noqa: F401 from .common import ZeroPad2D # noqa: F401 from .common import Pad3D # noqa: F401 from .common import CosineSimilarity # noqa: F401 from .common import Embedding # noqa: F401 from .common import Linear # noqa: F401 from .common import Identity # noqa: F401 from .common import Flatten # noqa: F401 from .common import Upsample # noqa: F401 from .common import Dropout # noqa: F401 from .common import Dropout2D # noqa: F401 from .common import Dropout3D # noqa: F401 from .common import AlphaDropout # noqa: F401 from .common import Upsample # noqa: F401 from .common import UpsamplingBilinear2D # noqa: F401 from .common import UpsamplingNearest2D # noqa: F401 from .common import Fold from .pooling import AvgPool1D # noqa: F401 from .pooling import AvgPool2D # noqa: F401 from .pooling import AvgPool3D # noqa: F401 from .pooling import MaxPool1D # noqa: F401 from .pooling import MaxPool2D # noqa: F401 from .pooling import MaxPool3D # noqa: F401 from .pooling import AdaptiveAvgPool1D # noqa: F401 from .pooling import AdaptiveAvgPool2D # noqa: F401 from .pooling import AdaptiveAvgPool3D # noqa: F401 from .pooling import AdaptiveMaxPool1D # noqa: F401 from .pooling import AdaptiveMaxPool2D # noqa: F401 from .pooling import AdaptiveMaxPool3D # noqa: F401 from .pooling import MaxUnPool1D # noqa: F401 from .pooling import MaxUnPool2D # noqa: F401 from .pooling import MaxUnPool3D # noqa: F401 from .conv import Conv1D # noqa: F401 from .conv import Conv2D # noqa: F401 from .conv import Conv3D # noqa: F401 from .conv import Conv1DTranspose # noqa: F401 from .conv import Conv2DTranspose # noqa: F401 from .conv import Conv3DTranspose # noqa: F401 from .loss import BCEWithLogitsLoss # noqa: F401 from .loss import CrossEntropyLoss # noqa: F401 from .loss import MSELoss # noqa: F401 from .loss import L1Loss # noqa: F401 from .loss import NLLLoss # noqa: F401 from .loss import BCELoss # noqa: F401 from .loss import KLDivLoss # noqa: F401 from .loss import MarginRankingLoss # noqa: F401 from .loss import MultiLabelSoftMarginLoss from .loss import CTCLoss # noqa: F401 from .loss import SmoothL1Loss # noqa: F401 from .loss import HingeEmbeddingLoss # noqa: F401 from .loss import TripletMarginWithDistanceLoss from .loss import TripletMarginLoss from .loss import SoftMarginLoss from .norm import BatchNorm1D # noqa: F401 from .norm import BatchNorm2D # noqa: F401 from .norm import BatchNorm3D # noqa: F401 from .norm import SyncBatchNorm # noqa: F401 from .norm import GroupNorm # noqa: F401 from .norm import LayerNorm # noqa: F401 from .norm import SpectralNorm # noqa: F401 from .norm import LocalResponseNorm # noqa: F401 from .vision import PixelShuffle # noqa: F401 from .vision import PixelUnshuffle # noqa: F401 from .vision import ChannelShuffle # noqa: F401 from .distance import PairwiseDistance # noqa: F401 from .container import LayerDict # noqa: F401 __all__ = []