[GitHub] vishaalkapoor edited a comment on issue #13757: Set ImageNet data augmentation by default

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vishaalkapoor edited a comment on issue #13757: Set ImageNet data augmentation by default
URL: https://github.com/apache/incubator-mxnet/pull/13757#issuecomment-452083992
 
 
   I'm unsure why image net arguments are not the default for a training script for image net and would be curious to know why not, but there are two better approaches to this depending on what is determined.
   
   If ImageNet arguments are to be the default, they should be merged into the stanza:
   ```
       parser.set_defaults(
           # network
           network          = 'resnet',
           num_layers       = 50,
           # data
           num_classes      = 1000,
           num_examples     = 1281167,
           image_shape      = '3,224,224',
           min_random_scale = 1, # if input image has min size k, suggest to use
                                 # 256.0/x, e.g. 0.533 for 480
           # train
           num_epochs       = 80,
           lr_step_epochs   = '30,60',
           dtype            = 'float32'
       )
   ```
   If they are not the default, it would be cleaner to add an argument --override-with-image-net-augmentations or something more appropriately named that would override parameters with those in the method.
   
   Vishaal

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