update train config (#6633)

deploy/auto_compression/configs/yolov5_s_qat_dis.yml

@@ -20,13 +20,11 @@ Quantization:
   - depthwise_conv2d
 
 TrainConfig:
-  train_iter: 5000
+  train_iter: 3000
   eval_iter: 1000
-  learning_rate:
-    type: CosineAnnealingDecay
-    learning_rate: 0.00003
-    T_max: 6000
+  learning_rate: 0.00001
   optimizer_builder:
     optimizer:
       type: SGD
     weight_decay: 4.0e-05
+  target_metric: 0.365

deploy/auto_compression/configs/yolov6mt_reader.yml

-metric: COCO
-num_classes: 80
-
-# Datset configuration
-TrainDataset:
-  !COCODataSet
-    image_dir: train2017
-    anno_path: annotations/instances_train2017.json
-    dataset_dir: dataset/coco/
-
-EvalDataset:
-  !COCODataSet
-    image_dir: val2017
-    anno_path: annotations/instances_val2017.json
-    dataset_dir: dataset/coco/
-
-worker_num: 0
-
-# preprocess reader in test
-EvalReader:
-  sample_transforms:
-    - Decode: {}
-    - Resize: {target_size:  [640, 640], keep_ratio: True, interp: 1}
-    - Pad: {size:  [640, 640], fill_value: [114., 114., 114.]}
-    - Permute: {}
-  batch_size: 1

deploy/auto_compression/configs/yolov6mt_s_qat_dis.yaml

 
 Global:
-  reader_config: configs/yolov6mt_reader.yml
+  reader_config: configs/yolov5_reader.yml
   input_list: ['image', 'scale_factor']
   arch: YOLO
   Evaluation: True
@@ -13,21 +13,19 @@ Distillation:
   loss: soft_label
 
 Quantization:
-  use_pact: true
   activation_quantize_type: 'moving_average_abs_max'
   quantize_op_types:
   - conv2d
   - depthwise_conv2d
 
 TrainConfig:
-  train_iter: 5000
+  train_iter: 8000
   eval_iter: 1000
   learning_rate: 
     type: CosineAnnealingDecay 
     learning_rate: 0.00003
-    T_max: 6000
+    T_max: 8000
   optimizer_builder:
     optimizer:
       type: SGD
-    weight_decay: 4.0e-05
-
+    weight_decay: 0.00004

deploy/auto_compression/configs/yolov7_l_qat_dis.yaml

 
 Global:
-  reader_config: configs/yolov7_reader.yml
+  reader_config: configs/yolov5_reader.yml
   input_list: ['image', 'scale_factor']
   arch: YOLO
   Evaluation: True
@@ -13,21 +13,19 @@ Distillation:
   loss: soft_label
 
 Quantization:
-  use_pact: true
   activation_quantize_type: 'moving_average_abs_max'
   quantize_op_types:
   - conv2d
   - depthwise_conv2d
 
 TrainConfig:
-  train_iter: 5000
+  train_iter: 8000
   eval_iter: 1000
   learning_rate: 
     type: CosineAnnealingDecay 
     learning_rate: 0.00003
-    T_max: 6000
+    T_max: 8000
   optimizer_builder:
     optimizer:
       type: SGD
-    weight_decay: 4.0e-05
-
+    weight_decay: 0.00004
\ No newline at end of file

deploy/auto_compression/configs/yolov7_reader.yml

-metric: COCO
-num_classes: 80
-
-# Datset configuration
-TrainDataset:
-  !COCODataSet
-    image_dir: train2017
-    anno_path: annotations/instances_train2017.json
-    dataset_dir: dataset/coco/
-
-EvalDataset:
-  !COCODataSet
-    image_dir: val2017
-    anno_path: annotations/instances_val2017.json
-    dataset_dir: dataset/coco/
-
-worker_num: 0
-
-# preprocess reader in test
-EvalReader:
-  sample_transforms:
-    - Decode: {}
-    - Resize: {target_size:  [640, 640], keep_ratio: True, interp: 1}
-    - Pad: {size:  [640, 640], fill_value: [114., 114., 114.]}
-    - Permute: {}
-  batch_size: 1

deploy/auto_compression/configs/yolox_reader.yml

-metric: COCO
-num_classes: 80
-
-# Datset configuration
-TrainDataset:
-  !COCODataSet
-    image_dir: train2017
-    anno_path: annotations/instances_train2017.json
-    dataset_dir: dataset/coco/
-
-EvalDataset:
-  !COCODataSet
-    image_dir: val2017
-    anno_path: annotations/instances_val2017.json
-    dataset_dir: dataset/coco/
-
-worker_num: 0
-
-# preprocess reader in test
-TestReader:
-  sample_transforms:
-    - Decode: {}
-    - Resize: {target_size: [640, 640], keep_ratio: True, interp: 1}
-    - Pad: {size: [640, 640], fill_value: [114., 114., 114.]}
-    - Permute: {}
-  batch_size: 1

deploy/auto_compression/configs/yolox_s_qat_dis.yaml

-
-Global:
-  reader_config: configs/yolox_reader.yml
-  input_list: ['image', 'scale_factor']
-  arch: YOLO
-  Evaluation: True
-  model_dir: ./yolox_s_300e_coco
-  model_filename: model.pdmodel
-  params_filename: model.pdiparams
-
-Distillation:
-  alpha: 1.0
-  loss: soft_label
-
-Quantization:
-  use_pact: true
-  activation_quantize_type: 'moving_average_abs_max'
-  quantize_op_types:
-  - conv2d
-  - depthwise_conv2d
-
-TrainConfig:
-  train_iter: 5000
-  eval_iter: 1000
-  learning_rate:  
-    type: CosineAnnealingDecay
-    learning_rate: 0.00003
-    T_max: 6000
-  optimizer_builder:
-    optimizer: 
-      type: SGD
-    weight_decay: 4.0e-05
-