mirror of
https://github.com/firestar5683/StarPilot.git
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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.
92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
import unittest, struct
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from tinygrad import Tensor, dtypes
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from tinygrad.uop.ops import UOp
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# format types: https://docs.python.org/3/library/struct.html
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class TestTensorBytes(unittest.TestCase):
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def test_bytes(self):
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lst = Tensor(bytes(b"\xaa\xbb\xcc\xdd"))
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assert lst.tolist() == [170, 187, 204, 221]
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def test_float_bytes(self):
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lst = Tensor(bytes(struct.pack("ff", 0.234, 0.8585)), dtype=dtypes.float32)
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assert lst.shape == (2,)
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assert abs(lst.tolist()[0] - 0.234) < 1e-6
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assert abs(lst.tolist()[1] - 0.8585) < 1e-6
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class TestTensorData(unittest.TestCase):
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def test_data(self):
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a = Tensor([1,2,3,4], dtype=dtypes.int32)
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dat = a.data()
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assert dat.itemsize == 4
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assert list(dat) == [1,2,3,4]
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assert dat.shape == (4,)
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assert dat[0] == 1
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assert dat[1] == 2
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def test_data_empty(self):
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a = Tensor([], dtype=dtypes.int32)
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dat = a.data()
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assert dat.itemsize == 4
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assert list(dat) == []
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assert dat.shape == (0,)
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def test_data_empty_multi_dim(self):
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a = Tensor([], dtype=dtypes.int32).reshape(0, 2)
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dat = a.data()
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assert dat.itemsize == 4
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assert list(dat) == []
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assert dat.shape == (0,)
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def test_data_uint8(self):
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a = Tensor([1,2,3,4], dtype=dtypes.uint8)
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dat = a.data()
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assert dat.format == "B"
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assert dat.itemsize == 1
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assert dat[0] == 1
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assert dat[1] == 2
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def test_data_nested(self):
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a = Tensor([[1,2],[3,4]], dtype=dtypes.int32)
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dat = a.data()
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assert dat.format == "i"
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assert dat.itemsize == 4
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assert dat.tolist() == [[1, 2], [3, 4]]
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assert dat.shape == (2,2)
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assert dat[0, 0] == 1
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assert dat[1, 1] == 4
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def test_data_const(self):
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a = Tensor(3, dtype=dtypes.int32)
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dat = a.data()
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assert dat.format == "i"
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assert dat.itemsize == 4
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assert dat.tolist() == 3
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assert dat.shape == ()
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def test_const_dtype_for_uop(self):
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self.assertEqual(Tensor.const(UOp.const(1.0).cast(dtypes.float32), dtypes.int8).dtype, dtypes.int8)
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self.assertEqual(Tensor.const(UOp.variable("x", 1, 10).bind(5), dtypes.int32).item(), 5)
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def test_data_float32(self):
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a = Tensor([[1,2.5],[3,4]], dtype=dtypes.float32)
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dat = a.data()
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assert dat.format == "f"
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assert dat[0, 1] == 2.5
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@unittest.skip("requires python 3.12")
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def test_data_float16(self):
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a = Tensor([[1,2.5],[3,4]], dtype=dtypes.float16)
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dat = a.data()
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assert dat.format == "e"
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assert dat.shape == (2,2)
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# NOTE: python can't deref float16
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def test_tolist_empty_shapes(self):
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for shape, expected in (((0,), []), ((2, 0), [[], []]), ((0, 2), []),
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((2, 0, 3), [[], []]), ((2, 3, 0), [[[], [], []], [[], [], []]])):
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self.assertEqual(Tensor.ones(*shape).tolist(), expected)
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if __name__ == '__main__':
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unittest.main() |