diff --git a/ppcls/modeling/architectures/efficientnet.py b/ppcls/modeling/architectures/efficientnet.py index 0a0ec2eaa1df8789952e029cfe68c85d05645458..33135839d8ff3247b8f228946111c97ce1f31e68 100644 --- a/ppcls/modeling/architectures/efficientnet.py +++ b/ppcls/modeling/architectures/efficientnet.py @@ -1,16 +1,16 @@ -#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # -#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 +# 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. +# 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. from __future__ import absolute_import from __future__ import division @@ -201,7 +201,8 @@ class EfficientNet(): def _expand_conv_norm(self, inputs, block_args, is_test, name=None): # Expansion phase - oup = block_args.input_filters * block_args.expand_ratio # number of output channels + oup = block_args.input_filters * \ + block_args.expand_ratio # number of output channels if block_args.expand_ratio != 1: conv = self.conv_bn_layer( @@ -223,7 +224,8 @@ class EfficientNet(): s = block_args.stride if isinstance(s, list) or isinstance(s, tuple): s = s[0] - oup = block_args.input_filters * block_args.expand_ratio # number of output channels + oup = block_args.input_filters * \ + block_args.expand_ratio # number of output channels conv = self.conv_bn_layer( inputs, @@ -326,7 +328,8 @@ class EfficientNet(): drop_connect_rate=None, name=None): # Expansion and Depthwise Convolution - oup = block_args.input_filters * block_args.expand_ratio # number of output channels + oup = block_args.input_filters * \ + block_args.expand_ratio # number of output channels has_se = self.use_se and (block_args.se_ratio is not None) and ( 0 < block_args.se_ratio <= 1) id_skip = block_args.id_skip # skip connection and drop connect diff --git a/ppcls/modeling/loss.py b/ppcls/modeling/loss.py index 0f967ce4386edba31b79942fbdd1447a07e4b922..fde986b5d8ad22f4be3f5b3033adb537157d4324 100644 --- a/ppcls/modeling/loss.py +++ b/ppcls/modeling/loss.py @@ -1,16 +1,16 @@ -#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # -#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 +# 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. +# 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. import paddle.fluid as fluid @@ -34,8 +34,7 @@ class Loss(object): def _labelsmoothing(self, target): if target.shape[-1] != self._class_dim: - one_hot_target = fluid.one_hot( - input=target, depth=self._class_dim) + one_hot_target = fluid.one_hot(input=target, depth=self._class_dim) else: one_hot_target = target soft_target = fluid.layers.label_smooth(