refine demos

config_demo1.yaml

@@ -12,4 +12,4 @@ learning_rate: 3e-5
 warmup_proportion: 0.1
 weight_decay: 0.1
 
-print_every_n_steps: 1
+print_every_n_steps: 10

config_demo2.yaml

 task_instance: "mrqa, mlm4mrqa, match4mrqa"
 target_tag: 1, 0, 0
-mix_ratio: 0.5, 1.0, 0.5
+mix_ratio: 1.0, 0.5, 0.5
 
 save_path: "output_model/secondrun"
 

config_demo3.yaml

@@ -12,7 +12,7 @@ do_lower_case: True
 max_seq_len: 512
 
 batch_size: 4
-num_epochs: 0.5
+num_epochs: 2
 optimizer: "adam"
 learning_rate: 3e-5
 warmup_proportion: 0.1

demo2.py

@@ -5,7 +5,7 @@ if __name__ == '__main__':
     controller.load_pretrain('pretrain_model/ernie/params')
     controller.train()
 
-    # controller = palm.Controller(config='config_demo2.yaml', task_dir='demo2_tasks', for_train=False)
-    # controller.pred('mrqa', inference_model_dir='output_model/secondrun/infer_model')
+    controller = palm.Controller(config='config_demo2.yaml', task_dir='demo2_tasks', for_train=False)
+    controller.pred('mrqa', inference_model_dir='output_model/secondrun/mrqa/infer_model')
 
 

demo2_tasks/mrqa.yaml

@@ -7,5 +7,3 @@ doc_stride: 128
 max_query_len: 64
 max_answer_len: 30
 n_best_size: 20
-null_score_diff_threshold: 0.0
-verbose: False

demo3.py

@@ -5,6 +5,3 @@ if __name__ == '__main__':
     controller.load_pretrain('pretrain_model/ernie/params')
     controller.train()
 
-    # controller = palm.Controller(config='config_demo3.yaml', task_dir='demo3_tasks', for_train=False)
-    # controller.pred('cls4mrqa', inference_model_dir='output_model/thirdrun/infer_model')
-

run_demo2.sh

-set -e
-export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-while true
-do
-    python -u demo2.py 
-done
-# GLOG_vmodule=lookup_table_op=4 python -u demo2.py > debug2.log 2>&1
+export CUDA_VISIBLE_DEVICES=0
+python demo2.py