BVLC_alexnet: added augmentation

diff --git a/models/bvlc_alexnet/solver_augment.prototxt b/models/bvlc_alexnet/solver_augment.prototxt
new file mode 100644 (file)
index 0000000..40120ea
--- /dev/null
+++ b/models/bvlc_alexnet/solver_augment.prototxt
@@ -0,0 +1,43 @@
+net: "models/bvlc_alexnet/train_val_augment.prototxt"
+
+test_iter: 196             #1562 = 50000/32
+test_interval:  1250   
+test_initialization: false
+
+display:  250
+
+max_iter: 125000 
+
+lr_policy: "poly"
+power: 2
+
+base_lr:   2                # B=1024
+
+#rampup_lr: 0.1
+#rampup_interval:  2500
+
+local_lr_auto: true
+local_gw_ratio: 0.001
+
+momentum: 0.9
+weight_decay: 0.0005
+
+snapshot: 500000
+snapshot_prefix: "models/bvlc_alexnet/snapshots/alexnet_fp32"
+snapshot_after_train: false
+
+solver_mode: GPU
+random_seed: 1
+
+# Train dataset size = 1,281,167
+# Test dataset size  =    50,000
+
+# batch 64  --> epoch = 20,000
+# batch 96  --> epoch = 15,000
+# batch 128 --> epoch = 10,000 
+# batch 256 --> epoch =  5,000  
+# batch 512 --> epoch =  2,500  
+# batch 1024--> epoch =  1,250
+# batch 2048--> epoch =    625
+# batch 4096--> epoch =    312
+# batch 8192--> epoch =    156

diff --git a/models/bvlc_alexnet/train_alexnet_augment.sh b/models/bvlc_alexnet/train_alexnet_augment.sh
new file mode 100755 (executable)
index 0000000..8ac7424
--- /dev/null
+++ b/models/bvlc_alexnet/train_alexnet_augment.sh
@@ -0,0 +1,5 @@
+#!/usr/bin/env sh
+
+./build/tools/caffe train \
+    --solver=models/bvlc_alexnet/solver_augment.prototxt -gpu=all \
+    2>&1 | tee models/bvlc_alexnet/logs/alexnet_augment_B1024_lr2.0.log

diff --git a/models/bvlc_alexnet/train_val_transform.prototxt b/models/bvlc_alexnet/train_val_augment.prototxt
similarity index 92%
rename from models/bvlc_alexnet/train_val_transform.prototxt
rename to models/bvlc_alexnet/train_val_augment.prototxt
index 8e724a5e1a676387e59141fa790165d9f4ebff44..d48fd5412d18a3da5a37f6d0276c37b8fcfbab8a 100644 (file)
--- a/models/bvlc_alexnet/train_val_transform.prototxt
+++ b/models/bvlc_alexnet/train_val_augment.prototxt
@@ -9,21 +9,17 @@ layer {
   top: "label"
   transform_param {
 #    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
+    mean_file: "data/imagenet/imagenet_mean.binaryproto"
+    img_rand_resize_lower: 240
+    img_rand_resize_upper: 272
     crop_size: 227
-    mean_value: 123.68
-    mean_value: 116.78
-    mean_value: 103.94
-    img_rand_resize_lower: 250
-    img_rand_resize_upper: 260
-    var_sz_img_enabled: true
     mirror: true
   }
   data_param {
     source: "examples/imagenet/ilsvrc12_train_lmdb"
-    batch_size: 256
-#    batch_size: 1024          # DGX1
+    batch_size: 1024          # DGX1
     backend: LMDB
-    cache: true
+    cache:   true
     shuffle: true
   }
   include { phase: TRAIN }
@@ -35,19 +31,16 @@ layer {
   top: "label"
   transform_param {
 #    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
-    crop_size: 227
-    mean_value: 123.68
-    mean_value: 116.78
-    mean_value: 103.94
+    mean_file: "data/imagenet/imagenet_mean.binaryproto"
     img_rand_resize_lower: 256
     img_rand_resize_upper: 256
-    var_sz_img_enabled: true
+    crop_size: 227
     mirror: false
   }
   data_param {
     source: "examples/imagenet/ilsvrc12_val_lmdb"
 #    batch_size: 32
-    batch_size: 256          # DGX1
+    batch_size: 256          
     backend: LMDB
   }
   include { phase: TEST }

diff --git a/models/resnet50/train_val_augment.prototxt b/models/resnet50/train_val_augment.prototxt
index 7e082006555615422ef8daeffe3c9e8c48dac981..7032c0c177c379a0f1b0784810a448d6eeb535c0 100644 (file)
--- a/models/resnet50/train_val_augment.prototxt
+++ b/models/resnet50/train_val_augment.prototxt
@@ -13,12 +13,9 @@ layer {
     shuffle: true  
   }
   transform_param {
-    var_sz_img_enabled: true
-    img_rand_resize_lower: 256
-    img_rand_resize_upper: 288
-    mean_value: 104
-    mean_value: 117
-    mean_value: 123
+    img_rand_resize_lower: 224
+    img_rand_resize_upper: 272
+    mean_file: "data/imagenet/imagenet_mean.binaryproto"
     crop_size: 224
     mirror: true
     scale: 0.00390625
@@ -36,9 +33,9 @@ layer {
     batch_size: 32
   }
   transform_param {
-    mean_value: 104
-    mean_value: 117
-    mean_value: 123
+    mean_file: "data/imagenet/imagenet_mean.binaryproto"
+    img_rand_resize_lower: 240
+    img_rand_resize_upper: 240
     crop_size: 224
     mirror: false
     scale: 0.00390625