forked from M-Labs/nac3
65 lines
1.4 KiB
Python
65 lines
1.4 KiB
Python
@extern
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def output_int32(x: int32):
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...
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@extern
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def output_float64(x: float):
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...
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def consume_ndarray_1(n: ndarray[float, Literal[1]]):
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pass
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def consume_ndarray_i32_1(n: ndarray[int32, Literal[1]]):
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pass
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def consume_ndarray_2(n: ndarray[float, Literal[2]]):
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pass
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def test_ndarray_ctor():
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n: ndarray[float, Literal[1]] = np_ndarray([1])
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consume_ndarray_1(n)
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def test_ndarray_empty():
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n: ndarray[float, 1] = np_empty([1])
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consume_ndarray_1(n)
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def test_ndarray_zeros():
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n: ndarray[float, 1] = np_zeros([1])
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output_float64(n[0])
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consume_ndarray_1(n)
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def test_ndarray_ones():
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n: ndarray[float, 1] = np_ones([1])
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output_float64(n[0])
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consume_ndarray_1(n)
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def test_ndarray_full():
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n_float: ndarray[float, 1] = np_full([1], 2.0)
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output_float64(n_float[0])
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consume_ndarray_1(n_float)
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n_i32: ndarray[int32, 1] = np_full([1], 2)
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output_int32(n_i32[0])
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consume_ndarray_i32_1(n_i32)
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def test_ndarray_eye():
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n: ndarray[float, 2] = np_eye(2)
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n0: ndarray[float, 1] = n[0]
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v: float = n0[0]
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output_float64(v)
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consume_ndarray_2(n)
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def test_ndarray_identity():
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n: ndarray[float, 2] = np_identity(2)
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consume_ndarray_2(n)
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def run() -> int32:
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test_ndarray_ctor()
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test_ndarray_empty()
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test_ndarray_zeros()
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test_ndarray_ones()
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test_ndarray_full()
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test_ndarray_eye()
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test_ndarray_identity()
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return 0
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