Fix save/load_inference_model, dataloader (#523)

* fix dataloader

demo/distillation/distill.py

@@ -121,6 +121,7 @@ def compress(args):
                 feed_list=[image, label],
                 drop_last=True,
                 batch_size=args.batch_size,
+                return_list=False,
                 shuffle=True,
                 use_shared_memory=False,
                 num_workers=1)
@@ -129,6 +130,7 @@ def compress(args):
                 places=place,
                 feed_list=[image, label],
                 drop_last=False,
+                return_list=False,
                 use_shared_memory=False,
                 batch_size=args.batch_size,
                 shuffle=False)
@@ -217,7 +219,7 @@ def compress(args):
                     format(epoch_id, step_id, val_loss[0], val_acc1[0],
                            val_acc5[0]))
         if args.save_inference:
-            paddle.static.save_inference_model(
+            paddle.fluid.io.save_inference_model(
                 os.path.join("./saved_models", str(epoch_id)), ["image"],
                 [out], exe, student_program)
         _logger.info("epoch {} top1 {:.6f}, top5 {:.6f}".format(

demo/prune/eval.py

@@ -65,6 +65,7 @@ def eval(args):
         places=place,
         feed_list=[image, label],
         drop_last=False,
+        return_list=False,
         batch_size=args.batch_size,
         shuffle=False)
 

demo/prune/train.py

@@ -150,6 +150,7 @@ def compress(args):
         drop_last=True,
         batch_size=args.batch_size,
         shuffle=True,
+        return_list=False,
         use_shared_memory=False,
         num_workers=16)
     valid_loader = paddle.io.DataLoader(
@@ -157,6 +158,7 @@ def compress(args):
         places=place,
         feed_list=[image, label],
         drop_last=False,
+        return_list=False,
         use_shared_memory=False,
         batch_size=args.batch_size,
         shuffle=False)

demo/quant/pact_quant_aware/train.py

@@ -426,7 +426,7 @@ def compress(args):
     if not os.path.isdir(model_path):
         os.makedirs(model_path)
 
-    paddle.static.save_inference_model(
+    paddle.fluid.io.save_inference_model(
         dirname=float_path,
         feeded_var_names=[image.name],
         target_vars=[out],

demo/quant/quant_aware/train.py

@@ -168,6 +168,7 @@ def compress(args):
         feed_list=[image, label],
         drop_last=True,
         batch_size=args.batch_size,
+        return_list=False,
         use_shared_memory=False,
         shuffle=True,
         num_workers=1)
@@ -176,6 +177,7 @@ 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)
@@ -277,7 +279,7 @@ def compress(args):
     if not os.path.isdir(model_path):
         os.makedirs(model_path)
 
-    paddle.static.save_inference_model(
+    paddle.fluid.io.save_inference_model(
         dirname=float_path,
         feeded_var_names=[image.name],
         target_vars=[out],

demo/quant/quant_post/eval.py

@@ -40,7 +40,7 @@ def eval(args):
     place = paddle.CUDAPlace(0) if args.use_gpu else paddle.CPUPlace()
     exe = paddle.static.Executor(place)
 
-    val_program, feed_target_names, fetch_targets = paddle.static.load_inference_model(
+    val_program, feed_target_names, fetch_targets = paddle.fluid.io.load_inference_model(
         args.model_path,
         exe,
         model_filename=args.model_name,

demo/quant/quant_post/export_model.py

@@ -62,7 +62,7 @@ def export_model(args):
     else:
         assert False, "args.pretrained_model must set"
 
-    paddle.static.save_inference_model(
+    paddle.fluid.io.save_inference_model(
         './inference_model/' + args.model,
         feeded_var_names=[image.name],
         target_vars=[out],

tests/test_analysis_helper.py

@@ -56,6 +56,7 @@ class TestAnalysisHelper(StaticCase):
             places=places,
             feed_list=[image, label],
             drop_last=True,
+            return_list=False,
             batch_size=64)
         exe.run(paddle.static.default_startup_program())
 

tests/test_quant_aware.py

@@ -124,9 +124,14 @@ class TestQuantAwareCase2(StaticCase):
             places=place,
             feed_list=[image, label],
             drop_last=True,
+            return_list=False,
             batch_size=64)
         valid_loader = paddle.io.DataLoader(
-            test_dataset, places=place, feed_list=[image, label], batch_size=64)
+            test_dataset,
+            places=place,
+            feed_list=[image, label],
+            batch_size=64,
+            return_list=False)
 
         def train(program):
             iter = 0

tests/test_quant_aware_user_defined.py

@@ -96,9 +96,14 @@ class TestQuantAwareCase1(StaticCase):
             places=place,
             feed_list=[image, label],
             drop_last=True,
+            return_list=False,
             batch_size=64)
         valid_loader = paddle.io.DataLoader(
-            test_dataset, places=place, feed_list=[image, label], batch_size=64)
+            test_dataset,
+            places=place,
+            feed_list=[image, label],
+            batch_size=64,
+            return_list=False)
 
         def train(program):
             iter = 0

tests/test_quant_post.py

@@ -60,9 +60,14 @@ class TestQuantAwareCase1(StaticCase):
             places=place,
             feed_list=[image, label],
             drop_last=True,
+            return_list=False,
             batch_size=64)
         valid_loader = paddle.io.DataLoader(
-            test_dataset, places=place, feed_list=[image, label], batch_size=64)
+            test_dataset,
+            places=place,
+            feed_list=[image, label],
+            batch_size=64,
+            return_list=False)
 
         def train(program):
             iter = 0
@@ -97,7 +102,7 @@ class TestQuantAwareCase1(StaticCase):
 
         train(main_prog)
         top1_1, top5_1 = test(val_prog)
-        paddle.static.save_inference_model(
+        paddle.fluid.io.save_inference_model(
             dirname='./test_quant_post',
             feeded_var_names=[image.name, label.name],
             target_vars=[avg_cost, acc_top1, acc_top5],
@@ -114,7 +119,7 @@ class TestQuantAwareCase1(StaticCase):
             model_filename='model',
             params_filename='params',
             batch_nums=10)
-        quant_post_prog, feed_target_names, fetch_targets = paddle.static.load_inference_model(
+        quant_post_prog, feed_target_names, fetch_targets = paddle.fluid.io.load_inference_model(
             dirname='./test_quant_post_inference',
             executor=exe,
             model_filename='__model__',

tests/test_quant_post_only_weight.py

@@ -60,9 +60,14 @@ class TestQuantPostOnlyWeightCase1(StaticCase):
             places=place,
             feed_list=[image, label],
             drop_last=True,
+            return_list=False,
             batch_size=64)
         valid_loader = paddle.io.DataLoader(
-            test_dataset, places=place, feed_list=[image, label], batch_size=64)
+            test_dataset,
+            places=place,
+            feed_list=[image, label],
+            batch_size=64,
+            return_list=False)
 
         def train(program):
             iter = 0
@@ -97,7 +102,7 @@ class TestQuantPostOnlyWeightCase1(StaticCase):
 
         train(main_prog)
         top1_1, top5_1 = test(val_prog)
-        paddle.static.save_inference_model(
+        paddle.fluid.io.save_inference_model(
             dirname='./test_quant_post_dynamic',
             feeded_var_names=[image.name, label.name],
             target_vars=[avg_cost, acc_top1, acc_top5],
@@ -112,7 +117,7 @@ class TestQuantPostOnlyWeightCase1(StaticCase):
             model_filename='model',
             params_filename='params',
             generate_test_model=True)
-        quant_post_prog, feed_target_names, fetch_targets = paddle.static.load_inference_model(
+        quant_post_prog, feed_target_names, fetch_targets = paddle.fluid.io.load_inference_model(
             dirname='./test_quant_post_inference/test_model', executor=exe)
         top1_2, top5_2 = test(quant_post_prog, fetch_targets)
         print("before quantization: top1: {}, top5: {}".format(top1_1, top5_1))