Why do I get different results when I resize the dataset before uploading it

Question

I am using the PyTorch framework to de the experiment. Normally I would use the code below to process the dataset before passing it to the neural network.

transforms.Resize(256), 
transforms.CenterCrop(224), 
transforms.ToTensor(), 
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])

But sometimes the dataset is too large, so I would use the transforms.Resize(256) to process the dataset before I upload it to the server. Then I only use the code below to process the dataset before passing it to the neural network.

transforms.CenterCrop(224), 
transforms.ToTensor(), 
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])

Theoretically, there two operations should be the same one, but normally I don't know why I would go different accuracy result.