Merge pull request PaddlePaddle#7143 from WenmuZhou/tttt

fix bug in amp eval

test_tipc/configs/det_r50_dcn_fce_ctw_v2_0/det_r50_vd_dcn_fce_ctw.yml

@@ -8,7 +8,7 @@ Global:
  # evaluation is run every 835 iterations
  eval_batch_step: [0, 4000]
  cal_metric_during_train: False
- pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained 
+ pretrained_model: pretrain_models/det_r50_dcn_fce_ctw_v2.0_train/best_accuracy.pdparams
  checkpoints: 
  save_inference_dir: 
  use_visualdl: False

test_tipc/configs/layoutxlm_ser/train_infer_python.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:ppstructure/docs/vqa/input/zh_val_42.jpg
 null:null
 ##
 trainer:norm_train
-norm_train:tools/train.py -c configs/vqa/ser/layoutxlm_xfund_zh.yml -o Global.print_batch_step=1 Global.eval_batch_step=[1000,1000] Train.loader.shuffle=false
+norm_train:tools/train.py -c configs/kie/layoutlm_series/ser_layoutlm_xfund_zh.yml -o Global.print_batch_step=1 Global.eval_batch_step=[1000,1000] Train.loader.shuffle=false
 pact_train:null
 fpgm_train:null
 distill_train:null
@@ -27,7 +27,7 @@ null:null
 ===========================infer_params===========================
 Global.save_inference_dir:./output/
 Architecture.Backbone.checkpoints:
-norm_export:tools/export_model.py -c configs/vqa/ser/layoutxlm_xfund_zh.yml -o 
+norm_export:tools/export_model.py -c configs/kie/layoutlm_series/ser_layoutlm_xfund_zh.yml -o 
 quant_export:
 fpgm_export: 
 distill_export:null

tools/program.py

@@ -372,7 +372,8 @@ def train(config,
  post_process_class,
  eval_class,
  model_type,
- extra_input=extra_input)
+ extra_input=extra_input,
+ scaler=scaler)
  cur_metric_str = 'cur metric, {}'.format(', '.join(
  ['{}: {}'.format(k, v) for k, v in cur_metric.items()]))
  logger.info(cur_metric_str)
@@ -462,7 +463,8 @@ def eval(model,
  post_process_class,
  eval_class,
  model_type=None,
- extra_input=False):
+ extra_input=False,
+ scaler=None):
  model.eval()
  with paddle.no_grad():
  total_frame = 0.0
@@ -479,12 +481,24 @@ def eval(model,
  break
  images = batch[0]
  start = time.time()
- if model_type == 'table' or extra_input:
- preds = model(images, data=batch[1:])
- elif model_type in ["kie", 'vqa']:
- preds = model(batch)
+
+ # use amp
+ if scaler:
+ with paddle.amp.auto_cast(level='O2'):
+ if model_type == 'table' or extra_input:
+ preds = model(images, data=batch[1:])
+ elif model_type in ["kie", 'vqa']:
+ preds = model(batch)
+ else:
+ preds = model(images)
  else:
- preds = model(images)
+ if model_type == 'table' or extra_input:
+ preds = model(images, data=batch[1:])
+ elif model_type in ["kie", 'vqa']:
+ preds = model(batch)
+ else:
+ preds = model(images)
+
  batch_numpy = []
  for item in batch:
  if isinstance(item, paddle.Tensor):