move datasets into datasets

test/test_mnist.py

@@ -6,16 +6,7 @@ from tinygrad.tensor import Tensor
 import tinygrad.optim as optim
 from extra.training import train, evaluate
 from extra.utils import fetch, get_parameters
-
-# mnist loader
-def fetch_mnist():
-  import gzip
-  parse = lambda file: np.frombuffer(gzip.open(file).read(), dtype=np.uint8).copy()
-  X_train = parse("test/mnist/train-images-idx3-ubyte.gz")[0x10:].reshape((-1, 28*28)).astype(np.float32)
-  Y_train = parse("test/mnist/train-labels-idx1-ubyte.gz")[8:]
-  X_test = parse("test/mnist/t10k-images-idx3-ubyte.gz")[0x10:].reshape((-1, 28*28)).astype(np.float32)
-  Y_test = parse("test/mnist/t10k-labels-idx1-ubyte.gz")[8:]
-  return X_train, Y_train, X_test, Y_test
+from datasets import fetch_mnist
 
 # load the mnist dataset
 X_train, Y_train, X_test, Y_test = fetch_mnist()