ThomasDelteil commented on a change in pull request #13099: [MXNET-1194] 
Reenable nightly tutorials tests for Python2 and Python3
URL: https://github.com/apache/incubator-mxnet/pull/13099#discussion_r230841563
 
 

 ##########
 File path: docs/tutorials/gluon/learning_rate_schedules.md
 ##########
 @@ -134,7 +134,7 @@ batch_size = 64
 
 # Load the training data
 train_dataset = 
mx.gluon.data.vision.MNIST(train=True).transform_first(transforms.ToTensor())
-train_dataloader = mx.gluon.data.DataLoader(train_dataset, batch_size, 
shuffle=True)
+train_dataloader = mx.gluon.data.DataLoader(train_dataset, batch_size, 
shuffle=True, num_workers=5)
 
 Review comment:
   @vishaalkapoor having too many workers for your DataLoader slows down your 
processing. Ideally your workers are in `[0, cpu_count - 2 - n_gpu]`
   You want to use 0 workers when your data is already in memory and 
pre-processed, for example an ArrayDataset that contains your data 
pre-transformed and ready to be fed to GPU.

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