mirror of
https://github.com/tinygrad/tinygrad.git
synced 2026-02-08 05:35:11 -05:00
1826ff6b89
* add dtype class * dtypes * buffers are lazy * dtype is tracked by lazybuffer and GenericShape * fix types in llvm * llvm store * dtype tests * fix tests maybe * fix flop counter * fix CI * CI fix and check format * fix dtype and dtype check * fix custom test * fix test graph
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
import unittest
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import numpy as np
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from tinygrad.helpers import getenv
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from tinygrad.lazy import Device
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from tinygrad.tensor import Tensor, dtypes
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# for GPU, cl_khr_fp16 isn't supported
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# for LLVM, it segfaults because it can't link to the casting function
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@unittest.skipIf(getenv("CI", "") != "" and Device.DEFAULT in ["GPU", "LLVM"], "float16 broken in some CI backends")
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class TestDtype(unittest.TestCase):
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def test_half_to_np(self):
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a = Tensor([1,2,3,4], dtype=dtypes.float16)
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print(a)
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na = a.numpy()
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print(na, na.dtype, a.lazydata.realized)
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assert na.dtype == np.float16
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def test_half_add(self):
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a = Tensor([1,2,3,4], dtype=dtypes.float16)
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b = Tensor([1,2,3,4], dtype=dtypes.float16)
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c = a+b
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print(c.numpy())
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assert c.dtype == dtypes.float16
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def test_upcast_float(self):
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# NOTE: there's no downcasting support
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a = Tensor([1,2,3,4], dtype=dtypes.float16).float()
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print(a)
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na = a.numpy()
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print(na, na.dtype)
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assert na.dtype == np.float32
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def test_half_add_upcast(self):
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a = Tensor([1,2,3,4], dtype=dtypes.float16)
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b = Tensor([1,2,3,4], dtype=dtypes.float32)
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c = a+b
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print(c.numpy())
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assert c.dtype == dtypes.float32
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if __name__ == '__main__':
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unittest.main() |