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I see in your code you're directly loading ImageNet dataset into a numpy array, does it mean you have a super large memory server, say 256GB? As to my knowledge ImageNet data is around 150GB large. Can you share why you're using .cvs form of imagenet data?
Appreciate for any response.
Thank you.
The text was updated successfully, but these errors were encountered:
@concerttttt Sorry for my late response. 🙏🏻
I recorded absolute paths of ImageNet images with csv format before training. So I loaded mini-batch images using generator (tf.data) during training, NOT loading whole images.
I see in your code you're directly loading ImageNet dataset into a numpy array, does it mean you have a super large memory server, say 256GB? As to my knowledge ImageNet data is around 150GB large. Can you share why you're using .cvs form of imagenet data?
Appreciate for any response.
Thank you.
The text was updated successfully, but these errors were encountered: