Organize hooks better in a dedicated HOOKS key in the config (#174)

Summary: Pull Request resolved: #174 vissl has many hooks that can be configured. but they were scattered all over the defaults.yaml unclear what parameter is a hook. reorganizing them under `HOOKS` for better readibility Reviewed By: min-xu-ai Differential Revision: D26284129 fbshipit-source-id: c71a69bb838cdb76d3e0594efddf584a5b3f8b68
facebookresearch · Feb 9, 2021 · cf65346 · cf65346
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diff --git a/GETTING_STARTED.md b/GETTING_STARTED.md
@@ -41,7 +41,7 @@ imagenet_full_size
 
 ### If VISSL is built from source
 We provide a config to train model using the pretext SimCLR task on the ResNet50 model.
-Change the `DATA.TRAIN.DATA_PATHS` path to the ImageNet train dataset folder path. 
+Change the `DATA.TRAIN.DATA_PATHS` path to the ImageNet train dataset folder path.
 
 ```bash
 cd $HOME/vissl
@@ -52,7 +52,7 @@ python3 tools/run_distributed_engines.py \
     config.DATA.TRAIN.DATA_PATHS=["/path/to/my/imagenet/folder/train"] \
     config=test/integration_test/quick_simclr_imagefolder \
     config.CHECKPOINT.DIR="./checkpoints" \
-    config.TENSORBOARD_SETUP.USE_TENSORBOARD=true
+    config.HOOKS.TENSORBOARD_SETUP.USE_TENSORBOARD=true
 ```
 
 ### If using pre-built conda/pip VISSL packages
@@ -100,7 +100,7 @@ python3 run_distributed_engines.py \
     config.DATA.TRAIN.DATA_PATHS=["/path/to/my/imagenet/folder/train"] \
     config=quick_1gpu_resnet50_simclr \
     config.CHECKPOINT.DIR="./checkpoints" \
-    config.TENSORBOARD_SETUP.USE_TENSORBOARD=true
+    config.HOOKS.TENSORBOARD_SETUP.USE_TENSORBOARD=true
 ```
 
 Explore **all the parameters and settings VISSL supports** in [VISSL defaults.yaml file](https://github.com/facebookresearch/vissl/blob/master/vissl/config/defaults.yaml)
diff --git a/configs/config/benchmark/imagenet1k_fulltune/eval_resnet_8gpu_transfer_in1k_fulltune.yaml b/configs/config/benchmark/imagenet1k_fulltune/eval_resnet_8gpu_transfer_in1k_fulltune.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...nchmark/linear_image_classification/imagenet1k/eval_resnet_8gpu_transfer_in1k_linear.yaml b/...nchmark/linear_image_classification/imagenet1k/eval_resnet_8gpu_transfer_in1k_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...ification/imagenet1k/other_styles/eval_resnet_final_output_8gpu_transfer_in1k_linear.yaml b/...ification/imagenet1k/other_styles/eval_resnet_final_output_8gpu_transfer_in1k_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...ge_classification/imagenet1k/other_styles/eval_resnet_moco_8gpu_transfer_in1k_linear.yaml b/...ge_classification/imagenet1k/other_styles/eval_resnet_moco_8gpu_transfer_in1k_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 28
     TRAIN:

diff --git a/...on/imagenet1k/other_styles/eval_resnet_res5_avgpool_output_8gpu_transfer_in1k_linear.yaml b/...on/imagenet1k/other_styles/eval_resnet_res5_avgpool_output_8gpu_transfer_in1k_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...ar_image_classification/inaturalist18/eval_resnet_8gpu_transfer_inaturalist18_linear.yaml b/...ar_image_classification/inaturalist18/eval_resnet_8gpu_transfer_inaturalist18_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 8
     TRAIN:

diff --git a/...k/linear_image_classification/openimages/eval_resnet_8gpu_transfer_openimages_linear.yaml b/...k/linear_image_classification/openimages/eval_resnet_8gpu_transfer_openimages_linear.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 2
     TRAIN:

diff --git a/...igs/config/benchmark/places205_fulltune/eval_resnet_8gpu_transfer_places205_fulltune.yaml b/...igs/config/benchmark/places205_fulltune/eval_resnet_8gpu_transfer_places205_fulltune.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...enchmark/semi_supervised/imagenet1k/eval_resnet_8gpu_transfer_in1k_semi_sup_fulltune.yaml b/...enchmark/semi_supervised/imagenet1k/eval_resnet_8gpu_transfer_in1k_semi_sup_fulltune.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...mark/semi_supervised/places205/eval_resnet_8gpu_transfer_places205_semi_sup_fulltune.yaml b/...mark/semi_supervised/places205/eval_resnet_8gpu_transfer_places205_semi_sup_fulltune.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/...gging/benchmark/linear_image_classification/eval_resnet_8gpu_transfer_imagenette_160.yaml b/...gging/benchmark/linear_image_classification/eval_resnet_8gpu_transfer_imagenette_160.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/debugging/pretrain/simclr/simclr_1node_resnet_imagenette_160.yaml b/configs/config/debugging/pretrain/simclr/simclr_1node_resnet_imagenette_160.yaml
@@ -6,8 +6,10 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
-  ROLLING_BTIME_FREQ: 313
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+      ROLLING_BTIME_FREQ: 313
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/clusterfit/clusterfit_resnet_8gpu_imagenet.yaml b/configs/config/pretrain/clusterfit/clusterfit_resnet_8gpu_imagenet.yaml
@@ -6,7 +6,9 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/deepcluster_v2/deepclusterv2_2crops_resnet.yaml b/configs/config/pretrain/deepcluster_v2/deepclusterv2_2crops_resnet.yaml
@@ -6,8 +6,10 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
-  ROLLING_BTIME_FREQ: 313
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+      ROLLING_BTIME_FREQ: 313
   DATA:
     NUM_DATALOADER_WORKERS: 8
     TRAIN:

diff --git a/configs/config/pretrain/jigsaw/jigsaw_8gpu_resnet.yaml b/configs/config/pretrain/jigsaw/jigsaw_8gpu_resnet.yaml
@@ -6,7 +6,9 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/moco/moco_1node_resnet.yaml b/configs/config/pretrain/moco/moco_1node_resnet.yaml
@@ -6,13 +6,15 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
-  ROLLING_BTIME_FREQ: 313
-  TENSORBOARD_SETUP:
-      USE_TENSORBOARD: True
-      EXPERIMENT_LOG_DIR: "moco_v2_reference"
-      LOG_PARAMS: False
-      FLUSH_EVERY_N_MIN: 20
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+      ROLLING_BTIME_FREQ: 313
+    TENSORBOARD_SETUP:
+        USE_TENSORBOARD: True
+        EXPERIMENT_LOG_DIR: "moco_v2_reference"
+        LOG_PARAMS: False
+        FLUSH_EVERY_N_MIN: 20
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/npid/npid++_4nodes_resnet.yaml b/configs/config/pretrain/npid/npid++_4nodes_resnet.yaml
@@ -6,7 +6,9 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 8
     TRAIN:

diff --git a/configs/config/pretrain/npid/npid_8gpu_resnet.yaml b/configs/config/pretrain/npid/npid_8gpu_resnet.yaml
@@ -6,7 +6,9 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/rotnet/rotnet_8gpu_resnet.yaml b/configs/config/pretrain/rotnet/rotnet_8gpu_resnet.yaml
@@ -7,7 +7,9 @@ config:
   TEST_MODEL: True
   SEED_VALUE: 1
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: False
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: False
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/simclr/models/efficientnet_B0.yaml b/configs/config/pretrain/simclr/models/efficientnet_B0.yaml
@@ -1,5 +1,9 @@
 # @package _global_
 config:
+  HOOKS:
+    MODEL_COMPLEXITY:
+      COMPUTE_COMPLEXITY: True
+      INPUT_SHAPE: [3, 224, 224]
   DATA:
     TRAIN:
       TRANSFORMS:
@@ -20,9 +24,6 @@ config:
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
   MODEL:
-    MODEL_COMPLEXITY:
-      COMPUTE_COMPLEXITY: True
-      INPUT_SHAPE: [3, 224, 224]
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/simclr/models/efficientnet_B1.yaml b/configs/config/pretrain/simclr/models/efficientnet_B1.yaml
@@ -19,10 +19,11 @@ config:
         - name: Normalize
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
-  MODEL:
+  HOOKS:
     MODEL_COMPLEXITY:
       COMPUTE_COMPLEXITY: True
       INPUT_SHAPE: [3, 240, 240]
+  MODEL:
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/simclr/models/efficientnet_B2.yaml b/configs/config/pretrain/simclr/models/efficientnet_B2.yaml
@@ -19,10 +19,11 @@ config:
         - name: Normalize
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
-  MODEL:
+  HOOKS:
     MODEL_COMPLEXITY:
       COMPUTE_COMPLEXITY: True
       INPUT_SHAPE: [3, 260, 260]
+  MODEL:
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/simclr/simclr_8node_resnet.yaml b/configs/config/pretrain/simclr/simclr_8node_resnet.yaml
@@ -6,8 +6,10 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
-  ROLLING_BTIME_FREQ: 313
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+      ROLLING_BTIME_FREQ: 313
   DATA:
     NUM_DATALOADER_WORKERS: 5
     TRAIN:

diff --git a/configs/config/pretrain/swav/models/efficientnet_B0.yaml b/configs/config/pretrain/swav/models/efficientnet_B0.yaml
@@ -20,10 +20,11 @@ config:
         - name: Normalize
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
-  MODEL:
+  HOOKS:
     MODEL_COMPLEXITY:
       COMPUTE_COMPLEXITY: True
       INPUT_SHAPE: [3, 224, 224]
+  MODEL:
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/swav/models/efficientnet_B1.yaml b/configs/config/pretrain/swav/models/efficientnet_B1.yaml
@@ -20,10 +20,11 @@ config:
         - name: Normalize
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
-  MODEL:
+  HOOKS:
     MODEL_COMPLEXITY:
       COMPUTE_COMPLEXITY: True
       INPUT_SHAPE: [3, 240, 240]
+  MODEL:
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/swav/models/efficientnet_B2.yaml b/configs/config/pretrain/swav/models/efficientnet_B2.yaml
@@ -20,10 +20,11 @@ config:
         - name: Normalize
           mean: [0.485, 0.456, 0.406]
           std: [0.229, 0.224, 0.225]
-  MODEL:
+  HOOKS:
     MODEL_COMPLEXITY:
       COMPUTE_COMPLEXITY: True
       INPUT_SHAPE: [3, 260, 260]
+  MODEL:
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS:

diff --git a/configs/config/pretrain/swav/swav_8node_resnet.yaml b/configs/config/pretrain/swav/swav_8node_resnet.yaml
@@ -6,8 +6,10 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
-  ROLLING_BTIME_FREQ: 313
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+      ROLLING_BTIME_FREQ: 313
   DATA:
     NUM_DATALOADER_WORKERS: 8
     TRAIN:

diff --git a/configs/config/test/cpu_test/test_cpu_efficientnet_simclr.yaml b/configs/config/test/cpu_test/test_cpu_efficientnet_simclr.yaml
@@ -6,7 +6,12 @@ config:
   TEST_MODEL: False
   SEED_VALUE: 0
   MULTI_PROCESSING_METHOD: forkserver
-  MONITOR_PERF_STATS: True
+  HOOKS:
+    PERF_STATS:
+      MONITOR_PERF_STATS: True
+    MODEL_COMPLEXITY:
+      COMPUTE_COMPLEXITY: False
+      INPUT_SHAPE: [3, 224, 224]
   DATA:
     NUM_DATALOADER_WORKERS: 0
     TRAIN:
@@ -40,9 +45,6 @@ config:
   METERS:
     name: ""
   MODEL:
-    MODEL_COMPLEXITY:
-      COMPUTE_COMPLEXITY: False
-      INPUT_SHAPE: [3, 224, 224]
     TRUNK:
       NAME: efficientnet
       TRUNK_PARAMS: