hetong007 commented on issue #11533: Fix image classification scripts and Improve Fp16 tutorial URL: https://github.com/apache/incubator-mxnet/pull/11533#issuecomment-406185114 For cifar training, the standard augmentation for benchmark is: ```python mean_rgb = [125.307, 122.961, 113.8575] std_rgb = [51.5865, 50.847, 51.255] train_data = mx.io.ImageRecordIter( path_imgrec = rec_train, path_imgidx = rec_train_idx, preprocess_threads = num_workers, shuffle = True, batch_size = batch_size, data_shape = (3, 32, 32), mean_r = mean_rgb[0], mean_g = mean_rgb[1], mean_b = mean_rgb[2], std_r = std_rgb[0], std_g = std_rgb[1], std_b = std_rgb[2], rand_mirror = True, pad = 4, fill_value = 0, rand_crop = True, max_crop_size = 32, min_crop_size = 32, ) val_data = mx.io.ImageRecordIter( path_imgrec = rec_val, path_imgidx = rec_val_idx, preprocess_threads = num_workers, shuffle = False, batch_size = batch_size, data_shape = (3, 32, 32), mean_r = mean_rgb[0], mean_g = mean_rgb[1], mean_b = mean_rgb[2], std_r = std_rgb[0], std_g = std_rgb[1], std_b = std_rgb[2], ) ``` Can you change accordingly?
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