[GitHub] juliusshufan edited a comment on issue #12362: Removing the re-size for validation data, which breaking the validation accuracy of CIFAR training

[GitBox]

juliusshufan edited a comment on issue #12362: Removing the re-size for 
validation data, which breaking the validation accuracy of CIFAR training
URL: https://github.com/apache/incubator-mxnet/pull/12362#issuecomment-419776997
 
 
   @zhreshold Thanks for the feedback, I use the pre-trained ResNet-50 model 
and validation-set of ImageNet-1k, and the accuracy with/w.o my changes are 
same: see test result:
   
   **Without** my changes:
   INFO:root:Finished with 126.286497 images per second
   INFO:root:('accuracy', 0.753156969309463)
   INFO:root:('top_k_accuracy_5', 0.9257512787723785)
   
   **With** my changes:
   INFO:root:Finished with 126.029153 images per second
   INFO:root:('accuracy', 0.753156969309463)
   INFO:root:('top_k_accuracy_5', 0.9257512787723785)
   
   The imagenet validation perf and accuracy are **same**.
   
   But **without** my changes, the validation accuracy trends of 
CIFAR10+ResNet50/VGG16 are as below, obviously it is not expected.
   
   
![image](https://user-images.githubusercontent.com/33112206/45274887-02611b00-b4ec-11e8-84ff-1dd02c93cff4.png)
   
![image](https://user-images.githubusercontent.com/33112206/45274907-2a507e80-b4ec-11e8-97c8-e3208d8dc0b0.png)
   

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