Fix pact demo dataloader (#526)

* fix bug

* code fix

demo/quant/pact_quant_aware/train.py

@@ -157,7 +157,9 @@ def compress(args):
         places=places,
         feed_list=[image, label],
         drop_last=True,
+        return_list=False,
         batch_size=args.batch_size,
+        use_shared_memory=False,
         shuffle=True,
         num_workers=1)
 
@@ -166,7 +168,9 @@ def compress(args):
         places=place,
         feed_list=[image, label],
         drop_last=False,
+        return_list=False,
         batch_size=args.batch_size,
+        use_shared_memory=False,
         shuffle=False)
 
     if args.analysis:
@@ -372,13 +376,8 @@ def compress(args):
         ckpt_path = args.checkpoint_dir
         assert args.checkpoint_epoch is not None, "checkpoint_epoch must be set"
         start_epoch = args.checkpoint_epoch
-        paddle.static.load_vars(
-            exe, dirname=args.checkpoint_dir, main_program=val_program)
-        start_step = start_epoch * int(
-            math.ceil(float(args.total_images) / args.batch_size))
-        v = paddle.static.global_scope().find_var(
-            '@LR_DECAY_COUNTER@').get_tensor()
-        v.set(np.array([start_step]).astype(np.float32), place)
+        paddle.static.load(
+            executor=exe, model_path=args.checkpoint_dir, program=val_program)
 
     best_eval_acc1 = 0
     best_acc1_epoch = 0
@@ -391,22 +390,20 @@ def compress(args):
         _logger.info("Best Validation Acc1: {:.6f}, at epoch {}".format(
             best_eval_acc1, best_acc1_epoch))
         paddle.static.save(
-            exe,
-            dirname=os.path.join(args.output_dir, str(i)),
-            main_program=val_program)
+            model_path=os.path.join(args.output_dir, str(i)),
+            program=val_program)
         if acc1 > best_acc1:
             best_acc1 = acc1
             best_epoch = i
             paddle.static.save(
-                exe,
-                dirname=os.path.join(args.output_dir, 'best_model'),
-                main_program=val_program)
+                model_path=os.path.join(args.output_dir, 'best_model'),
+                program=val_program)
 
-    if os.path.exists(os.path.join(args.output_dir, 'best_model')):
+    if os.path.exists(os.path.join(args.output_dir, 'best_model.pdparams')):
         paddle.static.load(
-            exe,
-            dirname=os.path.join(args.output_dir, 'best_model'),
-            main_program=val_program)
+            executor=exe,
+            model_path=os.path.join(args.output_dir, 'best_model'),
+            program=val_program)
 
     # 3. Freeze the graph after training by adjusting the quantize
     #    operators' order for the inference.

demo/quant/quant_aware/train.py

@@ -256,9 +256,9 @@ def compress(args):
                 model_path=os.path.join(args.checkpoint_dir, 'best_model'))
     if os.path.exists(os.path.join(args.checkpoint_dir, 'best_model')):
         paddle.static.load(
-            exe,
-            dirname=os.path.join(args.checkpoint_dir, 'best_model'),
-            main_program=val_program)
+            executor=exe,
+            model_path=os.path.join(args.checkpoint_dir, 'best_model'),
+            program=val_program)
     ############################################################################################################
     # 3. Freeze the graph after training by adjusting the quantize
     #    operators' order for the inference.