Clean up

Co-authored-by: The-Indian-Chinna <54074879+The-Indian-Chinna@users.noreply.github.com>

official/vision/beta/projects/yolo/configs/experiments/darknet53.yaml

@@ -9,33 +9,32 @@ task:
     backbone:
       type: 'darknet'
       darknet:
-        model_id: 'cspdarknet53'
+        model_id: 'darknet53'
   losses:
     l2_weight_decay: 0.0005
     one_hot: True
-    label_smoothing: 0.1
   train_data:
     tfds_name: 'imagenet_a'
     tfds_split: 'test'
     tfds_download: True
     is_training: True
-    global_batch_size: 128
+    global_batch_size: 2
     dtype: 'float16'
   validation_data:
     tfds_name: 'imagenet_a'
     tfds_split: 'test'
     tfds_download: True
     is_training: False
-    global_batch_size: 128
+    global_batch_size: 2
     dtype: 'float16'
     drop_remainder: False
 trainer:
-  train_steps: 800000 # in the paper
-  validation_steps: 400 # size of validation data
-  validation_interval: 10000
-  steps_per_loop: 10000
-  summary_interval: 10000
-  checkpoint_interval: 10000
+  train_steps: 51200000 # in the paper
+  validation_steps: 25600 # size of validation data
+  validation_interval: 150 
+  steps_per_loop: 150
+  summary_interval: 150
+  checkpoint_interval: 150
   optimizer_config:
     optimizer:
       type: 'sgd'
@@ -47,8 +46,8 @@ trainer:
         initial_learning_rate: 0.1
         end_learning_rate: 0.0001
         power: 4.0 
-        decay_steps: 799000
+        decay_steps: 51136000
     warmup:
       type: 'linear'
       linear:
-        warmup_steps: 1000 #lr rise from 0 to 0.1 over 1000 steps
+        warmup_steps: 64000 #lr rise from 0 to 0.1 over 1000 steps

official/vision/beta/projects/yolo/modeling/backbones/Darknet.py

@@ -157,10 +157,6 @@ BACKBONES = {
     "cspdarknettiny": CSPDARKNETTINY
 }
 
-CSPBlockConfig = collections.namedtuple('CSPBlockConfig', ['layer', 'stack', 'repetitions', 'bottleneck',
-  'filters', 'kernel_size', 'strides', 'padding', 'activation', 'route',
-  'output_name', 'is_output'])
-
 
 @ks.utils.register_keras_serializable(package='yolo')
 class Darknet(ks.Model):
@@ -181,10 +177,7 @@ class Darknet(ks.Model):
       config=None,
       **kwargs):
 
-    # layer_specs, splits = Darknet.get_config(model_id)
-    print(len(BACKBONES[model_id]['backbone'][-1]))
-    layer_specs = [CSPBlockConfig(*config) for config in BACKBONES[model_id]['backbone']]
-    splits = BACKBONES[model_id]['splits']
+    layer_specs, splits = Darknet.get_model_config(model_id)
 
     self._model_name = model_id
     self._splits = splits