fix the bug that the argument data_dir has no effect (#2415)

* modify single queue to a queue per process for data processing

* add transforms.py and rename torchvision_reader.py to reader.py

* add datasets.py

* remove pytorch apis

* fix some small bugs

* remove torch and torchvision from requirements.txt

* modify core.CUDAPlace to fluid.CUDAPlace

* bug fix: data_dir has no effect

* bug fix: data_dir has no effect

* bug fix: modify  in directory

* bug fix: fix a typo in README.md

PaddleCV/image_classification/fast_imagenet/README.md

@@ -19,7 +19,7 @@ PaddlePaddle Fast ImageNet using the dynmiac batch size, dynamic image size, rec
         |-train
         `-validation
     ```
-1. Install the requirements by `pip install -r requirement.txt`.
+1. Install the requirements by `pip install -r requirements.txt`.
 1. Launch the training job: `python train.py --data_dir /data/imagenet`
 1. Learning curve, we launch the training job on V100 GPU card:
 <p align="center">

PaddleCV/image_classification/fast_imagenet/train.py

@@ -292,9 +292,9 @@ def refresh_program(args,
 
 
 def prepare_reader(epoch_id, train_py_reader, train_bs, val_bs, trn_dir,
-                   img_dim, min_scale, rect_val):
+                   img_dim, min_scale, rect_val, args):
     train_reader = reader.train(
-        traindir="/data/imagenet/%strain" % trn_dir,
+        traindir="%s/%strain" % (args.data_dir, trn_dir),
         sz=img_dim,
         min_scale=min_scale,
         shuffle_seed=epoch_id + 1)
@@ -303,7 +303,7 @@ def prepare_reader(epoch_id, train_py_reader, train_bs, val_bs, trn_dir,
             train_reader, batch_size=train_bs))
 
     test_reader = reader.test(
-        valdir="/data/imagenet/%svalidation" % trn_dir,
+        valdir="%s/%svalidation" % (args.data_dir, trn_dir),
         bs=val_bs * DEVICE_NUM,
         sz=img_dim,
         rect_val=rect_val)
@@ -324,7 +324,7 @@ def train_parallel(args):
     ## dynamic batch size, image size...
     bs = 224
     val_bs = 64
-    trn_dir = "sz/160/"
+    trn_dir = "160/"
     img_dim = 128
     min_scale = 0.08
     rect_val = False
@@ -341,7 +341,7 @@ def train_parallel(args):
                 need_update_start_prog=True)
         elif epoch_id == 13:  #13
             bs = 96
-            trn_dir = "sz/352/"
+            trn_dir = "352/"
             img_dim = 224
             min_scale = 0.087
             train_args, test_args, test_prog, exe, test_exe = refresh_program(
@@ -384,7 +384,8 @@ def train_parallel(args):
             trn_dir,
             img_dim=img_dim,
             min_scale=min_scale,
-            rect_val=rect_val)
+            rect_val=rect_val,
+            args=args)
         train_py_reader.start()  # start pyreader
         batch_start_time = time.time()
         while True: