Major League Hacking Fellowship Merge (#295)

Summary: Pull Request resolved: #295 This is a coagulate merge, coordinated by prigoyal and uhbuhb. It addresses the following issues/pull requests: 1. MLH-Fellowship#7 2. MLH-Fellowship#8 3. MLH-Fellowship#9 4. MLH-Fellowship#10 5. MLH-Fellowship#13 6. MLH-Fellowship#14 Pull Request resolved: #221 Differential Revision: D27794128 Pulled By: prigoyal fbshipit-source-id: 4fa0322a902e446a02b46a2233eb54c6fac92f8f Co-authored-by: grace-omotoso
facebookresearch · Apr 15, 2021 · 7086542 · 7086542
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diff --git a/.gitignore b/.gitignore
@@ -38,6 +38,7 @@ var/
 .hydra/
 tb_logs/
 metrics.json
+stdout.json
 
 # PyInstaller
 #  Usually these files are written by a python script from a template
@@ -97,3 +98,4 @@ website/pages/tutorials/*
 
 # Configs for local development
 configs/config_local/*
+train_config.yaml
diff --git a/configs/config/benchmark/README.md b/configs/config/benchmark/README.md
@@ -43,9 +43,8 @@ MODEL:
     ]
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   HEAD:
     PARAMS: [
       ["eval_mlp", {"in_channels": 64, "dims": [9216, 1000]}],
@@ -73,9 +72,8 @@ MODEL:
     ]
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   HEAD:
     PARAMS: [
         ["mlp", {"dims": [2048, 1000]}],
@@ -95,9 +93,8 @@ MODEL:
     SHOULD_FLATTEN_FEATS: False
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   HEAD:
     PARAMS: [
       ["eval_mlp", {"in_channels": 2048, "dims": [2048, 1000]}],
@@ -124,9 +121,8 @@ MODEL:
     ]
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
 ```
 
 #### Train SVM on the trunk output
@@ -139,9 +135,8 @@ MODEL:
     EXTRACT_TRUNK_FEATURES_ONLY: True
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
 ```
 
 ### Nearest Neighbor
@@ -157,9 +152,8 @@ MODEL:
     SHOULD_FLATTEN_FEATS: False   # don't flatten the features and return as is
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   WEIGHTS_INIT:
     PARAMS_FILE: ""
     STATE_DICT_KEY_NAME: classy_state_dict
@@ -175,9 +169,8 @@ MODEL:
     EVAL_TRUNK_AND_HEAD: True  # initialized the model head as well from weights
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   HEAD:
     # SimCLR model head structure
     PARAMS: [
@@ -204,9 +197,8 @@ MODEL:
     ]
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   WEIGHTS_INIT:
     PARAMS_FILE: ""
     STATE_DICT_KEY_NAME: classy_state_dict
@@ -235,9 +227,8 @@ MODEL:
     ]
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
 ```
 
 #### Extract features of the trunk output
@@ -251,9 +242,8 @@ MODEL:
     SHOULD_FLATTEN_FEATS: False
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
 ```
 
 #### Extract features of the model head output (self-supervised head)
@@ -266,9 +256,8 @@ MODEL:
     EVAL_TRUNK_AND_HEAD: True
   TRUNK:
     NAME: resnet
-    TRUNK_PARAMS:
-      RESNETS:
-        DEPTH: 50
+    RESNETS:
+      DEPTH: 50
   HEAD:
     PARAMS: [
       ["mlp", {"dims": [2048, 2048], "use_relu": True}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/eval_resnet_8gpu_transfer_in1k_fulltune.yaml b/configs/config/benchmark/fulltune/imagenet1k/eval_resnet_8gpu_transfer_in1k_fulltune.yaml
@@ -58,9 +58,8 @@ config:
       EVAL_TRUNK_AND_HEAD: False
     TRUNK:
       NAME: resnet
-      TRUNK_PARAMS:
-        RESNETS:
-          DEPTH: 50
+      RESNETS:
+        DEPTH: 50
     HEAD:
       PARAMS: [
         ["mlp", {"dims": [2048, 1000]}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet128Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet128Gf.yaml
@@ -8,9 +8,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_128gf
+      REGNET:
+        name: regnet_y_128gf
     HEAD:
       PARAMS: [['mlp', {'dims': [7392, 1000]}]]
     SYNC_BN_CONFIG:

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet128Gf_swav_head.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet128Gf_swav_head.yaml
@@ -8,9 +8,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_128gf
+      REGNET:
+        name: regnet_y_128gf
     HEAD:
       PARAMS: [
         ["swav_head", {"normalize_feats": False, "skip_last_bn": False, "use_bn": True, "dims": [7392, 8192], "num_clusters": []}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [['mlp', {'dims': [3024, 1000]}]]
   DATA:

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_bn.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_bn.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [["eval_mlp", {"in_channels": 3024, "dims": [3024, 1000]}]]
       # PARAMS: [['mlp', {'dims': [3024, 1000]}]]

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [
         ["swav_head", {"dims": [3024, 4096], "use_bn": True, "num_clusters": []}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_d4096.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_d4096.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [
         ["swav_head", {"dims": [3024, 4096, 4096], "use_bn": True, "num_clusters": []}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_lastBN.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_lastBN.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [
         ["swav_head", {"dims": [3024, 4096], "use_bn": True, "skip_last_bn": False, "num_clusters": []}],

diff --git a/...onfig/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_lastBN_noNorm.yaml b/...onfig/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_lastBN_noNorm.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [
         ["swav_head", {"dims": [3024, 4096], "use_bn": True, "skip_last_bn": False, "normalize_feats": False, "num_clusters": []}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_noNorm.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet16Gf_swav_d3024_d4096_noNorm.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_16gf
+      REGNET:
+        name: regnet_y_16gf
     HEAD:
       PARAMS: [
         ["swav_head", {"dims": [3024, 4096], "use_bn": True, "normalize_feats": False, "num_clusters": []}],

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet256Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet256Gf.yaml
@@ -3,8 +3,7 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_256gf
+      REGNET:
+        name: regnet_y_256gf
     HEAD:
       PARAMS: [['mlp', {'dims': [5088, 1000]}]]
diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet256Gf_1.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet256Gf_1.yaml
@@ -8,13 +8,12 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          depth: 27
-          w_0: 640
-          w_a: 230.83
-          w_m: 2.53
-          group_width: 373
+      REGNET:
+        depth: 27
+        w_0: 640
+        w_a: 230.83
+        w_m: 2.53
+        group_width: 373
     HEAD:
       PARAMS: [['mlp', {'dims': [10444, 1000]}]]
     SYNC_BN_CONFIG:

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet32Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet32Gf.yaml
@@ -3,8 +3,7 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_32gf
+      REGNET:
+        name: regnet_y_32gf
     HEAD:
       PARAMS: [['mlp', {'dims': [3712, 1000]}]]
diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet32Gf_bn.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet32Gf_bn.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_32gf
+      REGNET:
+        name: regnet_y_32gf
     HEAD:
       PARAMS: [["eval_mlp", {"in_channels": 3712, "dims": [3712, 1000]}]]
       # PARAMS: [['mlp', {'dims': [3712, 1000]}]]
diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet64Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet64Gf.yaml
@@ -3,8 +3,7 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_64gf
+      REGNET:
+        name: regnet_y_64gf
     HEAD:
       PARAMS: [['mlp', {'dims': [2976, 1000]}]]
diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet64Gf_3.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet64Gf_3.yaml
@@ -8,13 +8,12 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          depth: 20
-          w_0: 352
-          w_a: 147.48
-          w_m: 2.4
-          group_width: 328
+      REGNET:
+        depth: 20
+        w_0: 352
+        w_a: 147.48
+        w_m: 2.4
+        group_width: 328
     HEAD:
       PARAMS: [['mlp', {'dims': [4920, 1000]}]]
     SYNC_BN_CONFIG:

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/regnet8Gf.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/regnet8Gf.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: regnet
-      TRUNK_PARAMS:
-        REGNET:
-          name: regnet_y_8gf
+      REGNET:
+        name: regnet_y_8gf
     HEAD:
       PARAMS: [['mlp', {'dims': [2016, 1000]}]]
   DATA:

diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/resnet50_w2.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/resnet50_w2.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: resnet
-      TRUNK_PARAMS:
-        RESNETS:
-          DEPTH: 50
-          WIDTH_MULTIPLIER: 2
+      RESNETS:
+        DEPTH: 50
+        WIDTH_MULTIPLIER: 2
     HEAD:
       PARAMS: [['mlp', {'dims': [4096, 1000]}]]
diff --git a/configs/config/benchmark/fulltune/imagenet1k/models/resnet50_w3.yaml b/configs/config/benchmark/fulltune/imagenet1k/models/resnet50_w3.yaml
@@ -3,9 +3,8 @@ config:
   MODEL:
     TRUNK:
       NAME: resnet
-      TRUNK_PARAMS:
-        RESNETS:
-          DEPTH: 50
-          WIDTH_MULTIPLIER: 3
+      RESNETS:
+        DEPTH: 50
+        WIDTH_MULTIPLIER: 3
     HEAD:
       PARAMS: [['mlp', {'dims': [6144, 1000]}]]