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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
15 lines
1.0 KiB
Python
15 lines
1.0 KiB
Python
from tinygrad.tensor import Tensor
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from tinygrad.nn.state import tar_extract
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def mnist(device=None, fashion=False):
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base_url = "http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/" if fashion else "https://storage.googleapis.com/cvdf-datasets/mnist/"
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def _mnist(file): return Tensor.from_url(base_url+file, gunzip=True)
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return _mnist("train-images-idx3-ubyte.gz")[0x10:].reshape(-1,1,28,28).to(device), _mnist("train-labels-idx1-ubyte.gz")[8:].to(device), \
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_mnist("t10k-images-idx3-ubyte.gz")[0x10:].reshape(-1,1,28,28).to(device), _mnist("t10k-labels-idx1-ubyte.gz")[8:].to(device)
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def cifar(device=None):
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tt = tar_extract(Tensor.from_url('https://data.brainchip.com/dataset-mirror/cifar10/cifar-10-binary.tar.gz', gunzip=True))
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train = Tensor.cat(*[tt[f"cifar-10-batches-bin/data_batch_{i}.bin"].reshape(-1, 3073).to(device) for i in range(1,6)])
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test = tt["cifar-10-batches-bin/test_batch.bin"].reshape(-1, 3073).to(device)
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return train[:, 1:].reshape(-1,3,32,32), train[:, 0], test[:, 1:].reshape(-1,3,32,32), test[:, 0]
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