修改空格等代码规范

docs/zh_CN/training/semi_supervised_learning/FixMatchCCSSL.md

@@ -33,13 +33,13 @@
         <td>pytorch版本</td>
         <td></td>
         <td></td>
-        <td></td>
+        <td>95.54</td>
     </tr>
     <tr>
         <td>paddle版本</td>
         <td></td>
         <td></td>
-        <td></td>
+        <td>95.61</td>
     </tr>
 </table>
 cifar10上，paddle版本的配置文件及训练好的模型如下表所示

ppcls/arch/__init__.py

@@ -14,8 +14,6 @@
 
 import copy
 import importlib
-from pyexpat import features
-
 import paddle.nn as nn
 from paddle.jit import to_static
 from paddle.static import InputSpec

ppcls/arch/backbone/model_zoo/wideresnet.py

@@ -235,4 +235,4 @@ def WideResNet(depth,
         num_classes=num_classes,
         proj=proj,
         low_dim=low_dim,
-        **kwargs)
+        **kwargs)

ppcls/configs/ssl/FixMatchCCSSL/FixMatchCCSSL_cifar100_10000_4gpu.yaml

@@ -30,8 +30,8 @@ Arch:
     name: WideResNet
     widen_factor: 8
     depth: 28
-    dropout: 0     # CCSSL为 drop_rate
-    num_classes: &sign_num_classes 100
+    dropout: 0 
+    num_classes: 100
     low_dim: 64
     proj: true
     proj_after: false
@@ -59,14 +59,6 @@ UnLabelLoss:
     - SoftSupConLoss:
         weight: 1.0
         temperature: 0.07
-    # - CCSSLLoss:
-    #     CELoss:
-    #       weight: 1.0
-    #       reduction: "none"
-    #     SoftSupConLoss:
-    #       weight: 1.0
-    #       temperature: 0.07
-    #     weight: 1.
 
 Optimizer:
   name: Momentum
@@ -80,8 +72,8 @@ Optimizer:
     num_training_steps: 524800
 
 DataLoader:
-  mean: &sign_mean [0.5071, 0.4867, 0.4408]
-  std: &sign_std [0.2675, 0.2565, 0.2761]
+  mean: [0.5071, 0.4867, 0.4408]
+  std: [0.2675, 0.2565, 0.2761]
   Train:
     dataset:
       name: CIFAR100SSL
@@ -99,11 +91,11 @@ DataLoader:
             padding_mode: "reflect"
         - ToTensor:
         - Normalize:
-            mean: *sign_mean
-            std: *sign_std
+            mean: [0.5071, 0.4867, 0.4408]
+            std: [0.2675, 0.2565, 0.2761]
     
     sampler:
-      name: DistributedBatchSampler    # DistributedBatchSampler
+      name: DistributedBatchSampler
       batch_size: 16
       drop_last: true
       shuffle: true
@@ -111,8 +103,6 @@ DataLoader:
       num_workers: 4
       use_shared_memory: true
   
-
-
   UnLabelTrain:
     dataset:
       name: CIFAR100SSL
@@ -129,8 +119,8 @@ DataLoader:
             padding_mode: 'reflect'
         - ToTensor:
         - Normalize:
-            mean: *sign_mean
-            std: *sign_std
+            mean: [0.5071, 0.4867, 0.4408]
+            std: [0.2675, 0.2565, 0.2761]
 
       transform_s1:
         - RandomHorizontalFlip:
@@ -144,8 +134,8 @@ DataLoader:
             m: 10
         - ToTensor:
         - Normalize:
-            mean: *sign_mean
-            std: *sign_std
+            mean: [0.5071, 0.4867, 0.4408]
+            std: [0.2675, 0.2565, 0.2761]
       
       transform_s2:
         - RandomResizedCrop:
@@ -163,12 +153,9 @@ DataLoader:
         - RandomGrayscale:
             p: 0.2
         - ToTensor:
-        # - Normalize:
-        #     mean: *sign_mean
-        #     std: *sign_std
 
     sampler:
-      name: DistributedBatchSampler   # DistributedBatchSampler
+      name: DistributedBatchSampler
       batch_size: 112
       drop_last: true
       shuffle: true
@@ -185,8 +172,8 @@ DataLoader:
       transform_ops:
         - ToTensor:
         - Normalize:
-            mean: *sign_mean
-            std: *sign_std
+            mean: [0.5071, 0.4867, 0.4408]
+            std: [0.2675, 0.2565, 0.2761]
     sampler:
       name: DistributedBatchSampler
       batch_size: 16
@@ -196,8 +183,6 @@ DataLoader:
       num_workers: 4
       use_shared_memory: true
 
-
-
 Metric:
   Eval:
     - TopkAcc:

ppcls/configs/ssl/FixMatchCCSSL/FixMatchCCSSL_cifar10_4000_4gpu.yaml

@@ -7,7 +7,7 @@ Global:
   eval_during_train: true
   eval_interval: 1
   epochs: 1024
-  iter_per_epoch: 40
+  iter_per_epoch: 1024
   print_batch_step: 20
   use_visualdl: false
   use_dali: false
@@ -196,8 +196,6 @@ DataLoader:
       num_workers: 4
       use_shared_memory: true
 
-
-
 Metric:
   Eval:
     - TopkAcc:

ppcls/data/preprocess/__init__.py

@@ -51,13 +51,10 @@ from paddle.vision.transforms import Pad as Pad_paddle_vision
 from ppcls.data.preprocess.batch_ops.batch_operators import MixupOperator, CutmixOperator, OpSampler, FmixOperator
 from ppcls.data.preprocess.batch_ops.batch_operators import MixupCutmixHybrid
 
-
-
 import numpy as np
 from PIL import Image
 import random
 
-
 def transform(data, ops=[]):
     """ transform """
     for op in ops:
@@ -120,5 +117,4 @@ class TimmAutoAugment(RawTimmAutoAugment):
         if isinstance(img, Image.Image):
             img = np.asarray(img)
 
-        return img
-        
+        return img

ppcls/engine/train/train_fixmatch_ccssl.py

@@ -1,7 +1,4 @@
-
-
 from __future__ import absolute_import, division, print_function
-
 import time
 from turtle import update
 import paddle
@@ -11,11 +8,11 @@ from ppcls.utils import profiler
 from paddle.nn import functional as F
 import numpy as np
 import paddle
-# from reprod_log import ReprodLogger
 
 
 def train_epoch_fixmatch_ccssl(engine, epoch_id, print_batch_step):
-
+    print(engine.model.state_dict().keys())
+    assert 1==0
     tic = time.time()
     if not hasattr(engine, 'train_dataloader_iter'):
         engine.train_dataloader_iter = iter(engine.train_dataloader)
@@ -135,5 +132,4 @@ def get_loss(engine,
             loss_dict[k] = v
     loss_dict['loss'] = loss_dict_label['loss'] + unlabel_loss['loss']
 
-    return loss_dict, logits_x
-    
+    return loss_dict, logits_x

ppcls/loss/softsuploss.py

@@ -1,7 +1,16 @@
-"""
-CCSSL loss
-author: zhhike
-"""
+#   Copyright (c) 2022 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.
 
 import paddle
 import paddle.nn as nn
@@ -65,5 +74,4 @@ class SoftSupConLoss(nn.Layer):
         if reduction == 'mean':
             loss = loss.mean()
 
-        return {"SoftSupConLoss": loss}
-    
+        return {"SoftSupConLoss": loss}