tinygrad/extra/datasets/preprocess_imagenet.py

from tinygrad import Tensor, dtypes
from extra.datasets.imagenet import iterate, get_val_files

if __name__ == "__main__":
  #sz = len(get_val_files())
  sz = 32*100
  X,Y = None, None

  idx = 0
  for x,y in iterate(shuffle=False):
    print(x.shape, y.shape, x.dtype, y.dtype)
    assert x.shape[0] == y.shape[0]
    bs = x.shape[0]
    if X is None:
      X = Tensor.empty(sz, *x.shape[1:], device="disk:/tmp/imagenet_x", dtype=dtypes.uint8)
      Y = Tensor.empty(sz, *y.shape[1:], device="disk:/tmp/imagenet_y", dtype=dtypes.int64)
      print(X.shape, Y.shape)
    X[idx:idx+bs].assign(x)
    Y[idx:idx+bs].assign(y)
    idx += bs
    if idx >= sz: break