forked from M-Labs/nac3
1903 lines
46 KiB
Python
1903 lines
46 KiB
Python
@extern
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def dbl_nan() -> float:
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...
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@extern
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def dbl_inf() -> float:
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...
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@extern
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def output_bool(x: bool):
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...
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@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_int64(x: int64):
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...
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@extern
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def output_uint32(x: uint32):
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...
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@extern
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def output_uint64(x: uint64):
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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 output_ndarray_bool_2(n: ndarray[bool, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_bool(n[r][c])
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def output_ndarray_int32_1(n: ndarray[int32, Literal[1]]):
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for i in range(len(n)):
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output_int32(n[i])
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def output_ndarray_int32_2(n: ndarray[int32, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_int32(n[r][c])
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def output_ndarray_int64_2(n: ndarray[int64, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_int64(n[r][c])
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def output_ndarray_uint32_2(n: ndarray[uint32, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_uint32(n[r][c])
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def output_ndarray_uint64_2(n: ndarray[uint64, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_uint64(n[r][c])
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def output_ndarray_float_1(n: ndarray[float, Literal[1]]):
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for i in range(len(n)):
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output_float64(n[i])
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def output_ndarray_float_2(n: ndarray[float, Literal[2]]):
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for r in range(len(n)):
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for c in range(len(n[r])):
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output_float64(n[r][c])
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def output_ndarray_float_3(n: ndarray[float, Literal[3]]):
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for d in range(len(n)):
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for r in range(len(n[d])):
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for c in range(len(n[d][r])):
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output_float64(n[d][r][c])
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def output_ndarray_float_4(n: ndarray[float, Literal[4]]):
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for x in range(len(n)):
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for y in range(len(n[x])):
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for z in range(len(n[x][y])):
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for w in range(len(n[x][y][z])):
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output_float64(n[x][y][z][w])
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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_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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n1: ndarray[float, 1] = np_empty([1])
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consume_ndarray_1(n1)
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n2: ndarray[float, 1] = np_empty(10)
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consume_ndarray_1(n2)
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n3: ndarray[float, 1] = np_empty((2,))
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consume_ndarray_1(n3)
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n4: ndarray[float, 2] = np_empty((4, 4))
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consume_ndarray_2(n4)
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dim4 = (5, 2)
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n5: ndarray[float, 2] = np_empty(dim4)
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consume_ndarray_2(n5)
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def test_ndarray_zeros():
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n1: ndarray[float, 1] = np_zeros([1])
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output_ndarray_float_1(n1)
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k = 3 + int32(n1[0]) # to test variable shape inputs
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n2: ndarray[float, 1] = np_zeros(k * k)
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output_ndarray_float_1(n2)
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n3: ndarray[float, 1] = np_zeros((k * 2,))
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output_ndarray_float_1(n3)
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dim4 = (3, 2 * k)
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n4: ndarray[float, 2] = np_zeros(dim4)
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output_ndarray_float_2(n4)
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def test_ndarray_ones():
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n: ndarray[float, 1] = np_ones([1])
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output_ndarray_float_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_ndarray_float_1(n_float)
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n_i32: ndarray[int32, 1] = np_full([1], 2)
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output_ndarray_int32_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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output_ndarray_float_2(n)
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def test_ndarray_array():
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n1: ndarray[float, 1] = np_array([1.0, 2.0, 3.0])
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output_ndarray_float_1(n1)
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n1to2: ndarray[float, 2] = np_array([1.0, 2.0, 3.0], ndmin=2)
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output_ndarray_float_2(n1to2)
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n2: ndarray[float, 2] = np_array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
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output_ndarray_float_2(n2)
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# Copy
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n2_cpy: ndarray[float, 2] = np_array(n2, copy=False)
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n2_cpy.fill(0.0)
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output_ndarray_float_2(n2_cpy)
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def test_ndarray_identity():
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n: ndarray[float, 2] = np_identity(2)
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output_ndarray_float_2(n)
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def test_ndarray_fill():
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n: ndarray[float, 2] = np_empty([2, 2])
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n.fill(1.0)
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output_ndarray_float_2(n)
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def test_ndarray_copy():
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x: ndarray[float, 2] = np_identity(2)
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y = x.copy()
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x.fill(0.0)
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_neg_idx():
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x = np_identity(2)
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for i in range(-1, -3, -1):
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for j in range(-1, -3, -1):
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output_float64(x[i][j])
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def test_ndarray_slices():
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x = np_identity(3)
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output_ndarray_float_2(x)
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x_identity = x[::]
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output_ndarray_float_2(x_identity)
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x02 = x[0::2]
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output_ndarray_float_2(x02)
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x_mirror = x[::-1]
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output_ndarray_float_2(x_mirror)
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x2 = x[0::2, 0::2]
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output_ndarray_float_2(x2)
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def test_ndarray_nd_idx():
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x = np_identity(2)
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x0: float = x[0, 0]
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output_float64(x0)
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output_float64(x[0, 1])
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output_float64(x[1, 0])
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output_float64(x[1, 1])
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def test_ndarray_transpose():
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x: ndarray[float, 2] = np_array([[1., 2., 3.], [4., 5., 6.]])
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y = np_transpose(x)
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z = np_transpose(y)
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output_int32(np_shape(x)[0])
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output_int32(np_shape(x)[1])
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output_ndarray_float_2(x)
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output_int32(np_shape(y)[0])
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output_int32(np_shape(y)[1])
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output_ndarray_float_2(y)
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output_int32(np_shape(z)[0])
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output_int32(np_shape(z)[1])
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output_ndarray_float_2(z)
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def test_ndarray_reshape():
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w: ndarray[float, 1] = np_array([1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])
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x = np_reshape(w, (1, 2, 1, -1))
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y = np_reshape(x, [2, -1])
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z = np_reshape(y, 10)
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output_int32(np_shape(w)[0])
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output_ndarray_float_1(w)
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output_int32(np_shape(x)[0])
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output_int32(np_shape(x)[1])
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output_int32(np_shape(x)[2])
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output_int32(np_shape(x)[3])
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output_ndarray_float_4(x)
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output_int32(np_shape(y)[0])
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output_int32(np_shape(y)[1])
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output_ndarray_float_2(y)
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output_int32(np_shape(z)[0])
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output_ndarray_float_1(z)
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x1: ndarray[int32, 1] = np_array([1, 2, 3, 4])
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x2: ndarray[int32, 2] = np_reshape(x1, (2, 2))
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output_int32(np_shape(x1)[0])
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output_ndarray_int32_1(x1)
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output_int32(np_shape(x2)[0])
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output_int32(np_shape(x2)[1])
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output_ndarray_int32_2(x2)
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def test_ndarray_broadcast_to():
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xs = np_array([1.0, 2.0, 3.0])
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ys = np_broadcast_to(xs, (1, 3))
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zs = np_broadcast_to(ys, (2, 4, 3))
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output_int32(np_shape(xs)[0])
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output_ndarray_float_1(xs)
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output_int32(np_shape(ys)[0])
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output_int32(np_shape(ys)[1])
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output_ndarray_float_2(ys)
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output_int32(np_shape(zs)[0])
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output_int32(np_shape(zs)[1])
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output_int32(np_shape(zs)[2])
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output_ndarray_float_3(zs)
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def test_ndarray_subscript_assignment():
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xs = np_array([[11.0, 22.0, 33.0, 44.0], [55.0, 66.0, 77.0, 88.0]])
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xs[0, 0] = 99.0
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output_ndarray_float_2(xs)
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xs[0] = 100.0
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output_ndarray_float_2(xs)
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xs[:, ::2] = 101.0
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output_ndarray_float_2(xs)
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xs[1:, 0] = 102.0
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output_ndarray_float_2(xs)
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xs[0] = np_array([-1.0, -2.0, -3.0, -4.0])
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output_ndarray_float_2(xs)
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xs[:] = np_array([-5.0, -6.0, -7.0, -8.0])
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output_ndarray_float_2(xs)
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# Test assignment with memory sharing
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ys1 = np_reshape(xs, (2, 4))
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ys2 = np_transpose(ys1)
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ys3 = ys2[::-1, 0]
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ys3[0] = -999.0
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output_ndarray_float_2(xs)
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output_ndarray_float_2(ys1)
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output_ndarray_float_2(ys2)
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output_ndarray_float_1(ys3)
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def test_ndarray_add():
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x = np_identity(2)
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y = x + np_ones([2, 2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_add_broadcast():
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x = np_identity(2)
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# y: ndarray[float, 2] = x + np_ones([2])
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y = x + np_ones([2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_add_broadcast_lhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = 1.0 + x
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y = 1.0 + x
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_add_broadcast_rhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = x + 1.0
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y = x + 1.0
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_iadd():
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x = np_identity(2)
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x += np_ones([2, 2])
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output_ndarray_float_2(x)
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def test_ndarray_iadd_broadcast():
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x = np_identity(2)
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x += np_ones([2])
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output_ndarray_float_2(x)
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def test_ndarray_iadd_broadcast_scalar():
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x = np_identity(2)
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x += 1.0
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output_ndarray_float_2(x)
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def test_ndarray_sub():
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x = np_ones([2, 2])
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y = x - np_identity(2)
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_sub_broadcast():
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x = np_identity(2)
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# y: ndarray[float, 2] = x - np_ones([2])
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y = x - np_ones([2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_sub_broadcast_lhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = 1.0 - x
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y = 1.0 - x
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_sub_broadcast_rhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = x - 1
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y = x - 1.0
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_isub():
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x = np_ones([2, 2])
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x -= np_identity(2)
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output_ndarray_float_2(x)
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def test_ndarray_isub_broadcast():
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x = np_identity(2)
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x -= np_ones([2])
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output_ndarray_float_2(x)
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def test_ndarray_isub_broadcast_scalar():
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x = np_identity(2)
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x -= 1.0
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output_ndarray_float_2(x)
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def test_ndarray_mul():
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x = np_ones([2, 2])
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y = x * np_identity(2)
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_mul_broadcast():
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x = np_identity(2)
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# y: ndarray[float, 2] = x * np_ones([2])
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y = x * np_ones([2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_mul_broadcast_lhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = 2.0 * x
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y = 2.0 * x
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_mul_broadcast_rhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = x * 2.0
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y = x * 2.0
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_imul():
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x = np_ones([2, 2])
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x *= np_identity(2)
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output_ndarray_float_2(x)
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def test_ndarray_imul_broadcast():
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x = np_identity(2)
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x *= np_ones([2])
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output_ndarray_float_2(x)
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def test_ndarray_imul_broadcast_scalar():
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x = np_identity(2)
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x *= 2.0
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output_ndarray_float_2(x)
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def test_ndarray_truediv():
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x = np_identity(2)
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y = x / np_ones([2, 2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_truediv_broadcast():
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x = np_identity(2)
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# y: ndarray[float, 2] = x / np_ones([2])
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y = x / np_ones([2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_truediv_broadcast_lhs_scalar():
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x = np_ones([2, 2])
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# y: ndarray[float, 2] = 2.0 / x
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y = 2.0 / x
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_truediv_broadcast_rhs_scalar():
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x = np_identity(2)
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# y: ndarray[float, 2] = x / 2.0
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y = x / 2.0
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
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def test_ndarray_itruediv():
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x = np_identity(2)
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x /= np_ones([2, 2])
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output_ndarray_float_2(x)
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def test_ndarray_itruediv_broadcast():
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x = np_identity(2)
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x /= np_ones([2])
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output_ndarray_float_2(x)
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def test_ndarray_itruediv_broadcast_scalar():
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x = np_identity(2)
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x /= 2.0
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output_ndarray_float_2(x)
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def test_ndarray_floordiv():
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x = np_identity(2)
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y = x // np_ones([2, 2])
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output_ndarray_float_2(x)
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output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_floordiv_broadcast():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x // np_ones([2])
|
|
y = x // np_ones([2])
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_floordiv_broadcast_lhs_scalar():
|
|
x = np_ones([2, 2])
|
|
# y: ndarray[float, 2] = 2.0 // x
|
|
y = 2.0 // x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_floordiv_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x // 2.0
|
|
y = x // 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_ifloordiv():
|
|
x = np_identity(2)
|
|
x //= np_ones([2, 2])
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_ifloordiv_broadcast():
|
|
x = np_identity(2)
|
|
x //= np_ones([2])
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_ifloordiv_broadcast_scalar():
|
|
x = np_identity(2)
|
|
x //= 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_mod():
|
|
x = np_identity(2)
|
|
y = x % np_full([2, 2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_mod_broadcast():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x % np_ones([2])
|
|
y = x % np_full([2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_mod_broadcast_lhs_scalar():
|
|
x = np_ones([2, 2])
|
|
# y: ndarray[float, 2] = 2.0 % x
|
|
y = 2.0 % x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_mod_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x % 2.0
|
|
y = x % 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_imod():
|
|
x = np_identity(2)
|
|
x %= np_full([2, 2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_imod_broadcast():
|
|
x = np_identity(2)
|
|
x %= np_full([2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_imod_broadcast_scalar():
|
|
x = np_identity(2)
|
|
x %= 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_pow():
|
|
x = np_identity(2)
|
|
y = x ** np_full([2, 2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_pow_broadcast():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x ** np_full([2], 2.0)
|
|
y = x ** np_full([2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_pow_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = 2.0 ** x
|
|
y = 2.0 ** x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_pow_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
# y: ndarray[float, 2] = x % 2.0
|
|
y = x ** 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_ipow():
|
|
x = np_identity(2)
|
|
x **= np_full([2, 2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_ipow_broadcast():
|
|
x = np_identity(2)
|
|
x **= np_full([2], 2.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_ipow_broadcast_scalar():
|
|
x = np_identity(2)
|
|
x **= 2.0
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_matmul():
|
|
# 2D @ 2D -> 2D
|
|
a1 = np_array([[2.0, 3.0], [5.0, 7.0]])
|
|
b1 = np_array([[11.0, 13.0], [17.0, 23.0]])
|
|
c1 = a1 @ b1
|
|
output_int32(np_shape(c1)[0])
|
|
output_int32(np_shape(c1)[1])
|
|
output_ndarray_float_2(c1)
|
|
|
|
# 1D @ 1D -> Scalar
|
|
a2 = np_array([2.0, 3.0, 5.0])
|
|
b2 = np_array([7.0, 11.0, 13.0])
|
|
c2 = a2 @ b2
|
|
output_float64(c2)
|
|
|
|
# 2D @ 1D -> 1D
|
|
a3 = np_array([[1.0, 2.0, 3.0], [7.0, 8.0, 9.0]])
|
|
b3 = np_array([4.0, 5.0, 6.0])
|
|
c3 = a3 @ b3
|
|
output_int32(np_shape(c3)[0])
|
|
output_ndarray_float_1(c3)
|
|
|
|
# 1D @ 2D -> 1D
|
|
a4 = np_array([1.0, 2.0, 3.0])
|
|
b4 = np_array([[4.0, 5.0], [6.0, 7.0], [8.0, 9.0]])
|
|
c4 = a4 @ b4
|
|
output_int32(np_shape(c4)[0])
|
|
output_ndarray_float_1(c4)
|
|
|
|
# Broadcasting
|
|
a5 = np_array([
|
|
[[ 0.0, 1.0, 2.0, 3.0],
|
|
[ 4.0, 5.0, 6.0, 7.0]],
|
|
[[ 8.0, 9.0, 10.0, 11.0],
|
|
[12.0, 13.0, 14.0, 15.0]],
|
|
[[16.0, 17.0, 18.0, 19.0],
|
|
[20.0, 21.0, 22.0, 23.0]]
|
|
])
|
|
b5 = np_array([
|
|
[[[ 0.0, 1.0, 2.0],
|
|
[ 3.0, 4.0, 5.0],
|
|
[ 6.0, 7.0, 8.0],
|
|
[ 9.0, 10.0, 11.0]]],
|
|
[[[12.0, 13.0, 14.0],
|
|
[15.0, 16.0, 17.0],
|
|
[18.0, 19.0, 20.0],
|
|
[21.0, 22.0, 23.0]]]
|
|
])
|
|
c5 = a5 @ b5
|
|
output_int32(np_shape(c5)[0])
|
|
output_int32(np_shape(c5)[1])
|
|
output_int32(np_shape(c5)[2])
|
|
output_int32(np_shape(c5)[3])
|
|
output_ndarray_float_4(c5)
|
|
|
|
def test_ndarray_imatmul():
|
|
x = np_identity(2)
|
|
x @= np_ones([2, 2])
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
def test_ndarray_pos():
|
|
x_int32 = np_full([2, 2], -2)
|
|
y_int32 = +x_int32
|
|
|
|
output_ndarray_int32_2(x_int32)
|
|
output_ndarray_int32_2(y_int32)
|
|
|
|
x_float = np_full([2, 2], -2.0)
|
|
y_float = +x_float
|
|
|
|
output_ndarray_float_2(x_float)
|
|
output_ndarray_float_2(y_float)
|
|
|
|
def test_ndarray_neg():
|
|
x_int32 = np_full([2, 2], -2)
|
|
y_int32 = -x_int32
|
|
|
|
output_ndarray_int32_2(x_int32)
|
|
output_ndarray_int32_2(y_int32)
|
|
|
|
x_float = np_full([2, 2], 2.0)
|
|
y_float = -x_float
|
|
|
|
output_ndarray_float_2(x_float)
|
|
output_ndarray_float_2(y_float)
|
|
|
|
def test_ndarray_inv():
|
|
x_int32 = np_full([2, 2], -2)
|
|
y_int32 = ~x_int32
|
|
|
|
output_ndarray_int32_2(x_int32)
|
|
output_ndarray_int32_2(y_int32)
|
|
|
|
x_bool = np_full([2, 2], True)
|
|
y_bool = ~x_bool
|
|
|
|
output_ndarray_bool_2(x_bool)
|
|
output_ndarray_bool_2(y_bool)
|
|
|
|
def test_ndarray_eq():
|
|
x = np_identity(2)
|
|
y = x == np_full([2, 2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_eq_broadcast():
|
|
x = np_identity(2)
|
|
y = x == np_full([2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_eq_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 0.0 == x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_eq_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x == 0.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ne():
|
|
x = np_identity(2)
|
|
y = x != np_full([2, 2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ne_broadcast():
|
|
x = np_identity(2)
|
|
y = x != np_full([2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ne_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 0.0 != x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ne_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x != 0.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_lt():
|
|
x = np_identity(2)
|
|
y = x < np_full([2, 2], 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_lt_broadcast():
|
|
x = np_identity(2)
|
|
y = x < np_full([2], 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_lt_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 1.0 < x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_lt_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x < 1.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_le():
|
|
x = np_identity(2)
|
|
y = x <= np_full([2, 2], 0.5)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_le_broadcast():
|
|
x = np_identity(2)
|
|
y = x <= np_full([2], 0.5)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_le_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 0.5 <= x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_le_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x <= 0.5
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_gt():
|
|
x = np_identity(2)
|
|
y = x > np_full([2, 2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_gt_broadcast():
|
|
x = np_identity(2)
|
|
y = x > np_full([2], 0.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_gt_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 0.0 > x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_gt_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x > 0.0
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ge():
|
|
x = np_identity(2)
|
|
y = x >= np_full([2, 2], 0.5)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ge_broadcast():
|
|
x = np_identity(2)
|
|
y = x >= np_full([2], 0.5)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ge_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
y = 0.5 >= x
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_ge_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
y = x >= 0.5
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_int32():
|
|
x = np_identity(2)
|
|
y = int32(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int32_2(y)
|
|
|
|
def test_ndarray_int64():
|
|
x = np_identity(2)
|
|
y = int64(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int64_2(y)
|
|
|
|
def test_ndarray_uint32():
|
|
x = np_identity(2)
|
|
y = uint32(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_uint32_2(y)
|
|
|
|
def test_ndarray_uint64():
|
|
x = np_identity(2)
|
|
y = uint64(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_uint64_2(y)
|
|
|
|
def test_ndarray_float():
|
|
x = np_full([2, 2], 1)
|
|
y = float(x)
|
|
|
|
output_ndarray_int32_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_bool():
|
|
x = np_identity(2)
|
|
y = bool(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(y)
|
|
|
|
def test_ndarray_round():
|
|
x = np_identity(2)
|
|
xf32 = round(x)
|
|
xf64 = round64(x)
|
|
xff = np_round(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int32_2(xf32)
|
|
output_ndarray_int64_2(xf64)
|
|
output_ndarray_float_2(xff)
|
|
|
|
def test_ndarray_floor():
|
|
x = np_identity(2)
|
|
xf32 = floor(x)
|
|
xf64 = floor64(x)
|
|
xff = np_floor(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int32_2(xf32)
|
|
output_ndarray_int64_2(xf64)
|
|
output_ndarray_float_2(xff)
|
|
|
|
def test_ndarray_ceil():
|
|
x = np_identity(2)
|
|
xf32 = ceil(x)
|
|
xf64 = ceil64(x)
|
|
xff = np_ceil(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int32_2(xf32)
|
|
output_ndarray_int64_2(xf64)
|
|
output_ndarray_float_2(xff)
|
|
|
|
def test_ndarray_min():
|
|
x = np_identity(2)
|
|
y = np_min(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_float64(y)
|
|
|
|
def test_ndarray_minimum():
|
|
x = np_identity(2)
|
|
min_x_zeros = np_minimum(x, np_zeros([2]))
|
|
min_x_ones = np_minimum(x, np_zeros([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(min_x_zeros)
|
|
output_ndarray_float_2(min_x_ones)
|
|
|
|
def test_ndarray_minimum_broadcast():
|
|
x = np_identity(2)
|
|
min_x_zeros = np_minimum(x, np_zeros([2]))
|
|
min_x_ones = np_minimum(x, np_zeros([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(min_x_zeros)
|
|
output_ndarray_float_2(min_x_ones)
|
|
|
|
def test_ndarray_minimum_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
min_x_zeros = np_minimum(0.0, x)
|
|
min_x_ones = np_minimum(1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(min_x_zeros)
|
|
output_ndarray_float_2(min_x_ones)
|
|
|
|
def test_ndarray_minimum_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
min_x_zeros = np_minimum(x, 0.0)
|
|
min_x_ones = np_minimum(x, 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(min_x_zeros)
|
|
output_ndarray_float_2(min_x_ones)
|
|
|
|
def test_ndarray_argmin():
|
|
x = np_array([[1., 2.], [3., 4.]])
|
|
y = np_argmin(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_int64(y)
|
|
|
|
def test_ndarray_max():
|
|
x = np_identity(2)
|
|
y = np_max(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_float64(y)
|
|
|
|
def test_ndarray_maximum():
|
|
x = np_identity(2)
|
|
max_x_zeros = np_maximum(x, np_zeros([2]))
|
|
max_x_ones = np_maximum(x, np_zeros([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(max_x_zeros)
|
|
output_ndarray_float_2(max_x_ones)
|
|
|
|
def test_ndarray_maximum_broadcast():
|
|
x = np_identity(2)
|
|
max_x_zeros = np_maximum(x, np_zeros([2]))
|
|
max_x_ones = np_maximum(x, np_zeros([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(max_x_zeros)
|
|
output_ndarray_float_2(max_x_ones)
|
|
|
|
def test_ndarray_maximum_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
max_x_zeros = np_maximum(0.0, x)
|
|
max_x_ones = np_maximum(1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(max_x_zeros)
|
|
output_ndarray_float_2(max_x_ones)
|
|
|
|
def test_ndarray_maximum_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
max_x_zeros = np_maximum(x, 0.0)
|
|
max_x_ones = np_maximum(x, 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(max_x_zeros)
|
|
output_ndarray_float_2(max_x_ones)
|
|
|
|
def test_ndarray_argmax():
|
|
x = np_array([[1., 2.], [3., 4.]])
|
|
y = np_argmax(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_int64(y)
|
|
|
|
def test_ndarray_abs():
|
|
x = np_identity(2)
|
|
y = abs(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_isnan():
|
|
x = np_identity(2)
|
|
x_isnan = np_isnan(x)
|
|
y = np_full([2, 2], dbl_nan())
|
|
y_isnan = np_isnan(y)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(x_isnan)
|
|
output_ndarray_float_2(y)
|
|
output_ndarray_bool_2(y_isnan)
|
|
|
|
def test_ndarray_isinf():
|
|
x = np_identity(2)
|
|
x_isinf = np_isinf(x)
|
|
y = np_full([2, 2], dbl_inf())
|
|
y_isinf = np_isinf(y)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_bool_2(x_isinf)
|
|
output_ndarray_float_2(y)
|
|
output_ndarray_bool_2(y_isinf)
|
|
|
|
def test_ndarray_sin():
|
|
x = np_identity(2)
|
|
y = np_sin(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_cos():
|
|
x = np_identity(2)
|
|
y = np_cos(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_exp():
|
|
x = np_identity(2)
|
|
y = np_exp(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_exp2():
|
|
x = np_identity(2)
|
|
y = np_exp2(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_log():
|
|
x = np_identity(2)
|
|
y = np_log(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_log10():
|
|
x = np_identity(2)
|
|
y = np_log10(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_log2():
|
|
x = np_identity(2)
|
|
y = np_log2(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_fabs():
|
|
x = -np_identity(2)
|
|
y = np_fabs(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_sqrt():
|
|
x = np_identity(2)
|
|
y = np_sqrt(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_rint():
|
|
x = np_identity(2)
|
|
y = np_rint(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_tan():
|
|
x = np_identity(2)
|
|
y = np_tan(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arcsin():
|
|
x = np_identity(2)
|
|
y = np_arcsin(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arccos():
|
|
x = np_identity(2)
|
|
y = np_arccos(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arctan():
|
|
x = np_identity(2)
|
|
y = np_arctan(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_sinh():
|
|
x = np_identity(2)
|
|
y = np_sinh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_cosh():
|
|
x = np_identity(2)
|
|
y = np_cosh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_tanh():
|
|
x = np_identity(2)
|
|
y = np_tanh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arcsinh():
|
|
x = np_identity(2)
|
|
y = np_arcsinh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arccosh():
|
|
x = np_identity(2)
|
|
y = np_arccosh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arctanh():
|
|
x = np_identity(2)
|
|
y = np_arctanh(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_expm1():
|
|
x = np_identity(2)
|
|
y = np_expm1(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_cbrt():
|
|
x = np_identity(2)
|
|
y = np_cbrt(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_erf():
|
|
x = np_identity(2)
|
|
y = sp_spec_erf(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_erfc():
|
|
x = np_identity(2)
|
|
y = sp_spec_erfc(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_gamma():
|
|
x = np_identity(2)
|
|
y = sp_spec_gamma(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_gammaln():
|
|
x = np_identity(2)
|
|
y = sp_spec_gammaln(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_j0():
|
|
x = np_identity(2)
|
|
y = sp_spec_j0(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_j1():
|
|
x = np_identity(2)
|
|
y = sp_spec_j1(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_arctan2():
|
|
x = np_identity(2)
|
|
zeros = np_zeros([2, 2])
|
|
ones = np_ones([2, 2])
|
|
atan2_x_zeros = np_arctan2(x, zeros)
|
|
atan2_x_ones = np_arctan2(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(zeros)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(atan2_x_zeros)
|
|
output_ndarray_float_2(atan2_x_ones)
|
|
|
|
def test_ndarray_arctan2_broadcast():
|
|
x = np_identity(2)
|
|
atan2_x_zeros = np_arctan2(x, np_zeros([2]))
|
|
atan2_x_ones = np_arctan2(x, np_ones([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(atan2_x_zeros)
|
|
output_ndarray_float_2(atan2_x_ones)
|
|
|
|
def test_ndarray_arctan2_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
atan2_x_zeros = np_arctan2(0.0, x)
|
|
atan2_x_ones = np_arctan2(1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(atan2_x_zeros)
|
|
output_ndarray_float_2(atan2_x_ones)
|
|
|
|
def test_ndarray_arctan2_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
atan2_x_zeros = np_arctan2(x, 0.0)
|
|
atan2_x_ones = np_arctan2(x, 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(atan2_x_zeros)
|
|
output_ndarray_float_2(atan2_x_ones)
|
|
|
|
def test_ndarray_copysign():
|
|
x = np_identity(2)
|
|
ones = np_ones([2, 2])
|
|
negones = np_full([2, 2], -1.0)
|
|
copysign_x_ones = np_copysign(x, ones)
|
|
copysign_x_negones = np_copysign(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(negones)
|
|
output_ndarray_float_2(copysign_x_ones)
|
|
output_ndarray_float_2(copysign_x_negones)
|
|
|
|
def test_ndarray_copysign_broadcast():
|
|
x = np_identity(2)
|
|
copysign_x_ones = np_copysign(x, np_ones([2]))
|
|
copysign_x_negones = np_copysign(x, np_full([2], -1.0))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(copysign_x_ones)
|
|
output_ndarray_float_2(copysign_x_negones)
|
|
|
|
def test_ndarray_copysign_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
copysign_x_ones = np_copysign(1.0, x)
|
|
copysign_x_negones = np_copysign(-1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(copysign_x_ones)
|
|
output_ndarray_float_2(copysign_x_negones)
|
|
|
|
def test_ndarray_copysign_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
copysign_x_ones = np_copysign(x, 1.0)
|
|
copysign_x_negones = np_copysign(x, -1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(copysign_x_ones)
|
|
output_ndarray_float_2(copysign_x_negones)
|
|
|
|
def test_ndarray_fmax():
|
|
x = np_identity(2)
|
|
ones = np_ones([2, 2])
|
|
negones = np_full([2, 2], -1.0)
|
|
fmax_x_ones = np_fmax(x, ones)
|
|
fmax_x_negones = np_fmax(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(negones)
|
|
output_ndarray_float_2(fmax_x_ones)
|
|
output_ndarray_float_2(fmax_x_negones)
|
|
|
|
def test_ndarray_fmax_broadcast():
|
|
x = np_identity(2)
|
|
fmax_x_ones = np_fmax(x, np_ones([2]))
|
|
fmax_x_negones = np_fmax(x, np_full([2], -1.0))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmax_x_ones)
|
|
output_ndarray_float_2(fmax_x_negones)
|
|
|
|
def test_ndarray_fmax_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
fmax_x_ones = np_fmax(1.0, x)
|
|
fmax_x_negones = np_fmax(-1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmax_x_ones)
|
|
output_ndarray_float_2(fmax_x_negones)
|
|
|
|
def test_ndarray_fmax_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
fmax_x_ones = np_fmax(x, 1.0)
|
|
fmax_x_negones = np_fmax(x, -1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmax_x_ones)
|
|
output_ndarray_float_2(fmax_x_negones)
|
|
|
|
def test_ndarray_fmin():
|
|
x = np_identity(2)
|
|
ones = np_ones([2, 2])
|
|
negones = np_full([2, 2], -1.0)
|
|
fmin_x_ones = np_fmin(x, ones)
|
|
fmin_x_negones = np_fmin(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(negones)
|
|
output_ndarray_float_2(fmin_x_ones)
|
|
output_ndarray_float_2(fmin_x_negones)
|
|
|
|
def test_ndarray_fmin_broadcast():
|
|
x = np_identity(2)
|
|
fmin_x_ones = np_fmin(x, np_ones([2]))
|
|
fmin_x_negones = np_fmin(x, np_full([2], -1.0))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmin_x_ones)
|
|
output_ndarray_float_2(fmin_x_negones)
|
|
|
|
def test_ndarray_fmin_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
fmin_x_ones = np_fmin(1.0, x)
|
|
fmin_x_negones = np_fmin(-1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmin_x_ones)
|
|
output_ndarray_float_2(fmin_x_negones)
|
|
|
|
def test_ndarray_fmin_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
fmin_x_ones = np_fmin(x, 1.0)
|
|
fmin_x_negones = np_fmin(x, -1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(fmin_x_ones)
|
|
output_ndarray_float_2(fmin_x_negones)
|
|
|
|
def test_ndarray_ldexp():
|
|
x = np_identity(2)
|
|
zeros = np_full([2, 2], 0)
|
|
ones = np_full([2, 2], 1)
|
|
ldexp_x_zeros = np_ldexp(x, zeros)
|
|
ldexp_x_ones = np_ldexp(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_int32_2(zeros)
|
|
output_ndarray_int32_2(ones)
|
|
output_ndarray_float_2(ldexp_x_zeros)
|
|
output_ndarray_float_2(ldexp_x_ones)
|
|
|
|
def test_ndarray_ldexp_broadcast():
|
|
x = np_identity(2)
|
|
ldexp_x_zeros = np_ldexp(x, np_full([2], 0))
|
|
ldexp_x_ones = np_ldexp(x, np_full([2], 1))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(ldexp_x_zeros)
|
|
output_ndarray_float_2(ldexp_x_ones)
|
|
|
|
def test_ndarray_ldexp_broadcast_lhs_scalar():
|
|
x = int32(np_identity(2))
|
|
ldexp_x_zeros = np_ldexp(0.0, x)
|
|
ldexp_x_ones = np_ldexp(1.0, x)
|
|
|
|
output_ndarray_int32_2(x)
|
|
output_ndarray_float_2(ldexp_x_zeros)
|
|
output_ndarray_float_2(ldexp_x_ones)
|
|
|
|
def test_ndarray_ldexp_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
ldexp_x_zeros = np_ldexp(x, 0)
|
|
ldexp_x_ones = np_ldexp(x, 1)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(ldexp_x_zeros)
|
|
output_ndarray_float_2(ldexp_x_ones)
|
|
|
|
def test_ndarray_hypot():
|
|
x = np_identity(2)
|
|
zeros = np_zeros([2, 2])
|
|
ones = np_ones([2, 2])
|
|
hypot_x_zeros = np_hypot(x, zeros)
|
|
hypot_x_ones = np_hypot(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(zeros)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(hypot_x_zeros)
|
|
output_ndarray_float_2(hypot_x_ones)
|
|
|
|
def test_ndarray_hypot_broadcast():
|
|
x = np_identity(2)
|
|
hypot_x_zeros = np_hypot(x, np_zeros([2]))
|
|
hypot_x_ones = np_hypot(x, np_ones([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(hypot_x_zeros)
|
|
output_ndarray_float_2(hypot_x_ones)
|
|
|
|
def test_ndarray_hypot_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
hypot_x_zeros = np_hypot(0.0, x)
|
|
hypot_x_ones = np_hypot(1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(hypot_x_zeros)
|
|
output_ndarray_float_2(hypot_x_ones)
|
|
|
|
def test_ndarray_hypot_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
hypot_x_zeros = np_hypot(x, 0.0)
|
|
hypot_x_ones = np_hypot(x, 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(hypot_x_zeros)
|
|
output_ndarray_float_2(hypot_x_ones)
|
|
|
|
def test_ndarray_nextafter():
|
|
x = np_identity(2)
|
|
zeros = np_zeros([2, 2])
|
|
ones = np_ones([2, 2])
|
|
nextafter_x_zeros = np_nextafter(x, zeros)
|
|
nextafter_x_ones = np_nextafter(x, ones)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(zeros)
|
|
output_ndarray_float_2(ones)
|
|
output_ndarray_float_2(nextafter_x_zeros)
|
|
output_ndarray_float_2(nextafter_x_ones)
|
|
|
|
def test_ndarray_nextafter_broadcast():
|
|
x = np_identity(2)
|
|
nextafter_x_zeros = np_nextafter(x, np_zeros([2]))
|
|
nextafter_x_ones = np_nextafter(x, np_ones([2]))
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(nextafter_x_zeros)
|
|
output_ndarray_float_2(nextafter_x_ones)
|
|
|
|
def test_ndarray_nextafter_broadcast_lhs_scalar():
|
|
x = np_identity(2)
|
|
nextafter_x_zeros = np_nextafter(0.0, x)
|
|
nextafter_x_ones = np_nextafter(1.0, x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(nextafter_x_zeros)
|
|
output_ndarray_float_2(nextafter_x_ones)
|
|
|
|
def test_ndarray_nextafter_broadcast_rhs_scalar():
|
|
x = np_identity(2)
|
|
nextafter_x_zeros = np_nextafter(x, 0.0)
|
|
nextafter_x_ones = np_nextafter(x, 1.0)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(nextafter_x_zeros)
|
|
output_ndarray_float_2(nextafter_x_ones)
|
|
|
|
def test_ndarray_dot():
|
|
x1: ndarray[float, 1] = np_array([5.0, 1.0, 4.0, 2.0])
|
|
y1: ndarray[float, 1] = np_array([5.0, 1.0, 6.0, 6.0])
|
|
z1 = np_dot(x1, y1)
|
|
|
|
x2: ndarray[int32, 1] = np_array([5, 1, 4, 2])
|
|
y2: ndarray[int32, 1] = np_array([5, 1, 6, 6])
|
|
z2 = np_dot(x2, y2)
|
|
|
|
x3: ndarray[bool, 1] = np_array([True, True, True, True])
|
|
y3: ndarray[bool, 1] = np_array([True, True, True, True])
|
|
z3 = np_dot(x3, y3)
|
|
|
|
z4 = np_dot(2, 3)
|
|
z5 = np_dot(2., 3.)
|
|
z6 = np_dot(True, False)
|
|
|
|
output_float64(z1)
|
|
output_int32(z2)
|
|
output_bool(z3)
|
|
output_int32(z4)
|
|
output_float64(z5)
|
|
output_bool(z6)
|
|
|
|
def test_ndarray_cholesky():
|
|
x: ndarray[float, 2] = np_array([[5.0, 1.0], [1.0, 4.0]])
|
|
y = np_linalg_cholesky(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_qr():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
y, z = np_linalg_qr(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
# QR Factorization is not unique and gives different results in numpy and nalgebra
|
|
# Reverting the decomposition to compare the initial arrays
|
|
a = y @ z
|
|
output_ndarray_float_2(a)
|
|
|
|
def test_ndarray_linalg_inv():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
y = np_linalg_inv(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_pinv():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
|
|
y = np_linalg_pinv(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_matrix_power():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
y = np_linalg_matrix_power(x, -9)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(y)
|
|
|
|
def test_ndarray_det():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
y = np_linalg_det(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_float64(y)
|
|
|
|
def test_ndarray_schur():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
t, z = sp_linalg_schur(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
# Schur Factorization is not unique and gives different results in scipy and nalgebra
|
|
# Reverting the decomposition to compare the initial arrays
|
|
a = (z @ t) @ np_linalg_inv(z)
|
|
output_ndarray_float_2(a)
|
|
|
|
def test_ndarray_hessenberg():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 5.0, 8.5]])
|
|
h, q = sp_linalg_hessenberg(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
|
|
# Hessenberg Factorization is not unique and gives different results in scipy and nalgebra
|
|
# Reverting the decomposition to compare the initial arrays
|
|
a = (q @ h) @ np_linalg_inv(q)
|
|
output_ndarray_float_2(a)
|
|
|
|
|
|
def test_ndarray_lu():
|
|
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
|
|
l, u = sp_linalg_lu(x)
|
|
|
|
output_ndarray_float_2(x)
|
|
output_ndarray_float_2(l)
|
|
output_ndarray_float_2(u)
|
|
|
|
|
|
def test_ndarray_svd():
|
|
w: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
|
|
x, y, z = np_linalg_svd(w)
|
|
|
|
output_ndarray_float_2(w)
|
|
|
|
# SVD Factorization is not unique and gives different results in numpy and nalgebra
|
|
# Reverting the decomposition to compare the initial arrays
|
|
a = x @ z
|
|
output_ndarray_float_2(a)
|
|
output_ndarray_float_1(y)
|
|
|
|
|
|
def run() -> int32:
|
|
test_ndarray_ctor()
|
|
test_ndarray_empty()
|
|
test_ndarray_zeros()
|
|
test_ndarray_ones()
|
|
test_ndarray_full()
|
|
test_ndarray_eye()
|
|
test_ndarray_array()
|
|
test_ndarray_identity()
|
|
test_ndarray_fill()
|
|
test_ndarray_copy()
|
|
|
|
test_ndarray_neg_idx()
|
|
test_ndarray_slices()
|
|
test_ndarray_nd_idx()
|
|
|
|
test_ndarray_transpose()
|
|
test_ndarray_reshape()
|
|
test_ndarray_broadcast_to()
|
|
test_ndarray_subscript_assignment()
|
|
|
|
test_ndarray_add()
|
|
test_ndarray_add_broadcast()
|
|
test_ndarray_add_broadcast_lhs_scalar()
|
|
test_ndarray_add_broadcast_rhs_scalar()
|
|
test_ndarray_iadd()
|
|
test_ndarray_iadd_broadcast()
|
|
test_ndarray_iadd_broadcast_scalar()
|
|
test_ndarray_sub()
|
|
test_ndarray_sub_broadcast()
|
|
test_ndarray_sub_broadcast_lhs_scalar()
|
|
test_ndarray_sub_broadcast_rhs_scalar()
|
|
test_ndarray_isub()
|
|
test_ndarray_isub_broadcast()
|
|
test_ndarray_isub_broadcast_scalar()
|
|
test_ndarray_mul()
|
|
test_ndarray_mul_broadcast()
|
|
test_ndarray_mul_broadcast_lhs_scalar()
|
|
test_ndarray_mul_broadcast_rhs_scalar()
|
|
test_ndarray_imul()
|
|
test_ndarray_imul_broadcast()
|
|
test_ndarray_imul_broadcast_scalar()
|
|
test_ndarray_truediv()
|
|
test_ndarray_truediv_broadcast()
|
|
test_ndarray_truediv_broadcast_lhs_scalar()
|
|
test_ndarray_truediv_broadcast_rhs_scalar()
|
|
test_ndarray_itruediv()
|
|
test_ndarray_itruediv_broadcast()
|
|
test_ndarray_itruediv_broadcast_scalar()
|
|
test_ndarray_floordiv()
|
|
test_ndarray_floordiv_broadcast()
|
|
test_ndarray_floordiv_broadcast_lhs_scalar()
|
|
test_ndarray_floordiv_broadcast_rhs_scalar()
|
|
test_ndarray_ifloordiv()
|
|
test_ndarray_ifloordiv_broadcast()
|
|
test_ndarray_ifloordiv_broadcast_scalar()
|
|
test_ndarray_mod()
|
|
test_ndarray_mod_broadcast()
|
|
test_ndarray_mod_broadcast_lhs_scalar()
|
|
test_ndarray_mod_broadcast_rhs_scalar()
|
|
test_ndarray_imod()
|
|
test_ndarray_imod_broadcast()
|
|
test_ndarray_imod_broadcast_scalar()
|
|
test_ndarray_pow()
|
|
test_ndarray_pow_broadcast()
|
|
test_ndarray_pow_broadcast_lhs_scalar()
|
|
test_ndarray_pow_broadcast_rhs_scalar()
|
|
test_ndarray_ipow()
|
|
test_ndarray_ipow_broadcast()
|
|
test_ndarray_ipow_broadcast_scalar()
|
|
test_ndarray_matmul()
|
|
test_ndarray_imatmul()
|
|
test_ndarray_pos()
|
|
test_ndarray_neg()
|
|
test_ndarray_inv()
|
|
test_ndarray_eq()
|
|
test_ndarray_eq_broadcast()
|
|
test_ndarray_eq_broadcast_lhs_scalar()
|
|
test_ndarray_eq_broadcast_rhs_scalar()
|
|
test_ndarray_ne()
|
|
test_ndarray_ne_broadcast()
|
|
test_ndarray_ne_broadcast_lhs_scalar()
|
|
test_ndarray_ne_broadcast_rhs_scalar()
|
|
test_ndarray_lt()
|
|
test_ndarray_lt_broadcast()
|
|
test_ndarray_lt_broadcast_lhs_scalar()
|
|
test_ndarray_lt_broadcast_rhs_scalar()
|
|
test_ndarray_lt()
|
|
test_ndarray_le_broadcast()
|
|
test_ndarray_le_broadcast_lhs_scalar()
|
|
test_ndarray_le_broadcast_rhs_scalar()
|
|
test_ndarray_gt()
|
|
test_ndarray_gt_broadcast()
|
|
test_ndarray_gt_broadcast_lhs_scalar()
|
|
test_ndarray_gt_broadcast_rhs_scalar()
|
|
test_ndarray_gt()
|
|
test_ndarray_ge_broadcast()
|
|
test_ndarray_ge_broadcast_lhs_scalar()
|
|
test_ndarray_ge_broadcast_rhs_scalar()
|
|
|
|
test_ndarray_int32()
|
|
test_ndarray_int64()
|
|
test_ndarray_uint32()
|
|
test_ndarray_uint64()
|
|
test_ndarray_float()
|
|
test_ndarray_bool()
|
|
|
|
test_ndarray_round()
|
|
test_ndarray_floor()
|
|
test_ndarray_ceil()
|
|
test_ndarray_min()
|
|
test_ndarray_minimum()
|
|
test_ndarray_minimum_broadcast()
|
|
test_ndarray_minimum_broadcast_lhs_scalar()
|
|
test_ndarray_minimum_broadcast_rhs_scalar()
|
|
test_ndarray_argmin()
|
|
test_ndarray_max()
|
|
test_ndarray_maximum()
|
|
test_ndarray_maximum_broadcast()
|
|
test_ndarray_maximum_broadcast_lhs_scalar()
|
|
test_ndarray_maximum_broadcast_rhs_scalar()
|
|
test_ndarray_argmax()
|
|
test_ndarray_abs()
|
|
test_ndarray_isnan()
|
|
test_ndarray_isinf()
|
|
|
|
test_ndarray_sin()
|
|
test_ndarray_cos()
|
|
test_ndarray_exp()
|
|
test_ndarray_exp2()
|
|
test_ndarray_log()
|
|
test_ndarray_log10()
|
|
test_ndarray_log2()
|
|
test_ndarray_fabs()
|
|
test_ndarray_sqrt()
|
|
test_ndarray_rint()
|
|
test_ndarray_tan()
|
|
test_ndarray_arcsin()
|
|
test_ndarray_arccos()
|
|
test_ndarray_arctan()
|
|
test_ndarray_sinh()
|
|
test_ndarray_cosh()
|
|
test_ndarray_tanh()
|
|
test_ndarray_arcsinh()
|
|
test_ndarray_arccosh()
|
|
test_ndarray_arctanh()
|
|
test_ndarray_expm1()
|
|
test_ndarray_cbrt()
|
|
|
|
test_ndarray_erf()
|
|
test_ndarray_erfc()
|
|
test_ndarray_gamma()
|
|
test_ndarray_gammaln()
|
|
test_ndarray_j0()
|
|
test_ndarray_j1()
|
|
|
|
test_ndarray_arctan2()
|
|
test_ndarray_arctan2_broadcast()
|
|
test_ndarray_arctan2_broadcast_lhs_scalar()
|
|
test_ndarray_arctan2_broadcast_rhs_scalar()
|
|
test_ndarray_copysign()
|
|
test_ndarray_copysign_broadcast()
|
|
test_ndarray_copysign_broadcast_lhs_scalar()
|
|
test_ndarray_copysign_broadcast_rhs_scalar()
|
|
test_ndarray_fmax()
|
|
test_ndarray_fmax_broadcast()
|
|
test_ndarray_fmax_broadcast_lhs_scalar()
|
|
test_ndarray_fmax_broadcast_rhs_scalar()
|
|
test_ndarray_fmin()
|
|
test_ndarray_fmin_broadcast()
|
|
test_ndarray_fmin_broadcast_lhs_scalar()
|
|
test_ndarray_fmin_broadcast_rhs_scalar()
|
|
test_ndarray_ldexp()
|
|
test_ndarray_ldexp_broadcast()
|
|
test_ndarray_ldexp_broadcast_lhs_scalar()
|
|
test_ndarray_ldexp_broadcast_rhs_scalar()
|
|
test_ndarray_hypot()
|
|
test_ndarray_hypot_broadcast()
|
|
test_ndarray_hypot_broadcast_lhs_scalar()
|
|
test_ndarray_hypot_broadcast_rhs_scalar()
|
|
test_ndarray_nextafter()
|
|
test_ndarray_nextafter_broadcast()
|
|
test_ndarray_nextafter_broadcast_lhs_scalar()
|
|
test_ndarray_nextafter_broadcast_rhs_scalar()
|
|
|
|
test_ndarray_dot()
|
|
test_ndarray_cholesky()
|
|
test_ndarray_qr()
|
|
test_ndarray_svd()
|
|
test_ndarray_linalg_inv()
|
|
test_ndarray_pinv()
|
|
test_ndarray_matrix_power()
|
|
test_ndarray_det()
|
|
test_ndarray_lu()
|
|
test_ndarray_schur()
|
|
test_ndarray_hessenberg()
|
|
return 0
|