add simclr config

configs/simclr/simclr_clas_r50.yaml

@@ -0,0 +1,72 @@
+epochs: 90
+output_dir: output_dir
+
+model:
+  name: Classification
+  backbone:
+    name: ResNet
+    depth: 50
+    with_pool: true
+    frozen_stages: 4
+  head:
+    name: ClasHead
+    with_avg_pool: false
+    in_channels: 4096
+
+dataloader:
+  train:
+    num_workers: 8
+    sampler:
+      batch_size: 128
+      shuffle: true
+      drop_last: False
+    dataset:
+      name: ImageNet
+      dataroot: data/ILSVRC2012/train
+      return_label: True
+      transforms:
+        - name: RandomResizedCrop
+          size: 224
+        - name: RandomHorizontalFlip
+        - name: Transpose
+        - name: NormalizeImage
+          scale: 1.0/255.0
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+  val:
+    num_workers: 8
+    sampler:
+      batch_size: 128
+      shuffle: false
+      drop_last: false
+    dataset:
+      name: ImageNet
+      dataroot: data/ILSVRC2012/val
+      return_label: True
+      transforms:
+        - name: Resize
+          size: 256
+        - name: CenterCrop
+          size: 224
+        - name: Transpose
+        - name: NormalizeImage
+          scale: 1.0/255.0
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+
+
+lr_scheduler:
+  name: MultiStepDecay
+  learning_rate: 1.6
+  milestones: [60, 80]
+
+optimizer:
+  name: Momentum
+  weight_decay: 0.0
+
+log_config:
+    name: LogHook
+    interval: 50
+
+custom_config:
+  - name: EvaluateHook

docs/Train_SimCLR_model.md

@@ -41,7 +41,7 @@ python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c c
 ##### Cifar10
 
 ```
-python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/simclr/simclr_r50_IM.yaml
+python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/simclr/simclr_r18_cifar10.yaml
 ```
 
 
@@ -68,12 +68,12 @@ python tools/passl2ppclas/convert.py --type res50 --checkpoint ${CHECKPOINT} --o
 
 #### Train:
 ```
-python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/moco/moco_clas_r50.yaml --pretrained ${WEIGHT_FILE}
+python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/simclr/simclr_clas_r50.yaml --pretrained ${WEIGHT_FILE}
 ```
 
 #### Evaluate:
 ```
-python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/moco/moco_clas_r50.yaml --load ${CLS_WEGHT_FILE} --evaluate-only
+python -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c configs/simclr/simclr_clas_r50.yaml --load ${CLS_WEGHT_FILE} --evaluate-only
 ```
 
 The trained linear weights in conjuction with the backbone weights can be found at [SimCLR linear](https://passl.bj.bcebos.com/models/simclr_r50_ep100_ckpt.pdparam).

passl/modeling/backbones/resnetsimclr.py

@@ -14,8 +14,10 @@
 
 import paddle
 import paddle.nn as nn
-from .resnetcifar import ResNet
-from .resnetcifar import BasicBlock, BottleneckBlock
+# from .resnetcifar import ResNet
+# from .resnetcifar import BasicBlock, BottleneckBlock
+from .resnetimagenet import ResNet
+from .resnetimagenet import BasicBlock, BottleneckBlock
 
 from .builder import BACKBONES
 from ...modules import init, freeze