remove num_workers (#4295)

dygraph/yolov3/reader.py

@@ -296,8 +296,7 @@ def train(size=416,
           total_iter=0,
           mixup_iter=0,
           random_sizes=[],
-          num_workers=8,
-          max_queue=32,
+          num_workers=1,
           use_multiprocess_reader=True,
           use_gpu=True):
     generator = dsr.get_reader('train', size, batch_size, shuffle, shuffle_seed,

dygraph/yolov3/train.py

@@ -142,7 +142,6 @@ def train():
             mixup_iter=mixup_iter * devices_num,
             random_sizes=random_sizes,
             use_multiprocess_reader=cfg.use_multiprocess_reader,
-            num_workers=cfg.worker_num,
             use_gpu=cfg.use_gpu)
         if args.use_data_parallel:
             train_reader = fluid.contrib.reader.distributed_batch_reader(train_reader)

dygraph/yolov3/utility.py

@@ -123,7 +123,6 @@ def parse_args():
     add_arg('data_dir',         str,    'dataset/coco',        "The data root path.")
     add_arg('start_iter',       int,    0,      "Start iteration.")
     add_arg('use_multiprocess_reader', bool,   True,   "whether use multiprocess reader.")
-    add_arg('worker_num',       int,   8,   "worker number for multiprocess reader.")
     add_arg('use_data_parallel', ast.literal_eval, False, "the flag indicating whether to use data parallel model to train the model")
     #SOLVER
     add_arg('batch_size',       int,    8,      "Mini-batch size per device.")