From 5a37683749057c3a43ad742fe2ea8929e89f04af Mon Sep 17 00:00:00 2001 From: littletomatodonkey Date: Wed, 24 Jun 2020 12:55:54 +0000 Subject: [PATCH] fix hrnet name --- ppcls/modeling/architectures/hrnet.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/ppcls/modeling/architectures/hrnet.py b/ppcls/modeling/architectures/hrnet.py index 32f06df6..2f09280b 100644 --- a/ppcls/modeling/architectures/hrnet.py +++ b/ppcls/modeling/architectures/hrnet.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 @@ -74,7 +74,7 @@ class HRNet(): tr3 = self.transition_layer(st3, channels_3, channels_4, name='tr3') st4 = self.stage(tr3, num_modules_4, channels_4, name='st4') - #classification + # classification last_cls = self.last_cls_out(x=st4, name='cls_head') y = last_cls[0] last_num_filters = [256, 512, 1024] @@ -273,7 +273,7 @@ class HRNet(): input=conv, num_channels=num_filters, reduction_ratio=16, - name=name + '_fc') + name="fc" + name) return fluid.layers.elementwise_add(x=residual, y=conv, act='relu') def bottleneck_block(self, @@ -312,7 +312,7 @@ class HRNet(): input=conv, num_channels=num_filters * 4, reduction_ratio=16, - name=name + '_fc') + name="fc" + name) return fluid.layers.elementwise_add(x=residual, y=conv, act='relu') def squeeze_excitation(self, @@ -325,7 +325,7 @@ class HRNet(): stdv = 1.0 / math.sqrt(pool.shape[1] * 1.0) squeeze = fluid.layers.fc( input=pool, - size=num_channels / reduction_ratio, + size=int(num_channels / reduction_ratio), act='relu', param_attr=fluid.param_attr.ParamAttr( initializer=fluid.initializer.Uniform(-stdv, stdv), -- GitLab