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28a8b72024
* Remove Interpreted device & remaining CPU/TORCH ref * Oops * supports_device was useful * Fix doc wording --------- Co-authored-by: chenyu <chenyu@fastmail.com>
66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
#!/usr/bin/env python
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import unittest
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import numpy as np
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from tinygrad.tensor import Tensor
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from tinygrad import dtypes
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N = 200 # has to be bigger than the cache to fail
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class TestAssign(unittest.TestCase):
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def test_simple_assignment(self):
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a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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a.realize()
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b.realize()
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ba1 = a.lazydata.base.realized
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bb1 = b.lazydata.base.realized
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a += b
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a.realize()
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ba2 = a.lazydata.base.realized
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assert ba1 == ba2 and ba1 != bb1
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np.testing.assert_allclose(a.numpy(), (np.arange(N*N)*2).reshape((N,N)))
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def test_permuted_assignment(self):
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a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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a.realize()
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b.realize()
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ba1 = a.lazydata.base.realized
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bb1 = b.lazydata.base.realized
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a = a.permute(1,0)
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a += b
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a.realize()
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ba2 = a.lazydata.base.realized
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assert ba1 != ba2 and ba1 != bb1
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np.testing.assert_allclose(a.numpy(), np.arange(N*N).reshape((N,N)) + np.arange(N*N).reshape((N,N)).transpose(1,0))
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def test_post_permuted_assignment(self):
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a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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a.realize()
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b.realize()
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#GlobalCounters.cache = []
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ba1 = a.lazydata.base.realized # noqa: F841
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bb1 = b.lazydata.base.realized # noqa: F841
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a.assign(a.permute(1,0) + b) # this should not work!
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a.realize()
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ba2 = a.lazydata.base.realized # noqa: F841
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# NOTE: don't test that it's assigned
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#assert ba1 == ba2 and ba1 != bb1
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np.testing.assert_allclose(a.numpy(), np.arange(N*N).reshape((N,N)) + np.arange(N*N).reshape((N,N)).transpose(1,0))
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# TODO: is there a way to sneak in a permute such that it returns the wrong answer?
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def test_cast_assignment(self):
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a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
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a.realize()
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oba1 = a.lazydata.base.output_buffer
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a.assign(a.cast(dtypes.int32).realize())
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a.realize()
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oba2 = a.lazydata.base.output_buffer
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assert oba1 is None and oba2 is None
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np.testing.assert_allclose(a.numpy(), np.arange(N*N,dtype=np.int32).reshape((N,N)))
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if __name__ == "__main__":
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unittest.main()
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