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nac3/nac3standalone/demo/src/ndarray.py

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core: Implement elementwise unary operators
2024-03-27 17:06:58 +08:00
@extern
def output_bool(x: bool):
...
core: Add test for indexing into ndarray
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@extern
def output_int32(x: int32):
...
@extern
def output_float64(x: float):
...
core: Implement elementwise unary operators
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def output_ndarray_bool_2(n: ndarray[bool, Literal[2]]):
for r in range(len(n)):
for c in range(len(n[r])):
output_bool(n[r][c])
core: Implement elementwise binary operators Including immediate variants of these operators.
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def output_ndarray_int32_1(n: ndarray[int32, Literal[1]]):
for i in range(len(n)):
output_int32(n[i])
core: Implement elementwise unary operators
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def output_ndarray_int32_2(n: ndarray[int32, Literal[2]]):
for r in range(len(n)):
for c in range(len(n[r])):
output_int32(n[r][c])
core: Implement elementwise binary operators Including immediate variants of these operators.
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def output_ndarray_float_1(n: ndarray[float, Literal[1]]):
for i in range(len(n)):
output_float64(n[i])
def output_ndarray_float_2(n: ndarray[float, Literal[2]]):
for r in range(len(n)):
for c in range(len(n[r])):
output_float64(n[r][c])
core: Implement ndarray constructor and numpy.empty
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def consume_ndarray_1(n: ndarray[float, Literal[1]]):
pass
def test_ndarray_ctor():
core: Fix Literal use in variable type annotation
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n: ndarray[float, Literal[1]] = np_ndarray([1])
core: Implement ndarray constructor and numpy.empty
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consume_ndarray_1(n)
def test_ndarray_empty():
core: Fix Literal use in variable type annotation
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n: ndarray[float, 1] = np_empty([1])
core: Implement ndarray constructor and numpy.empty
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consume_ndarray_1(n)
core: Implement most ndarray-creation functions
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def test_ndarray_zeros():
core: Fix Literal use in variable type annotation
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n: ndarray[float, 1] = np_zeros([1])
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_float_1(n)
core: Implement most ndarray-creation functions
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def test_ndarray_ones():
core: Fix Literal use in variable type annotation
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n: ndarray[float, 1] = np_ones([1])
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_float_1(n)
core: Implement most ndarray-creation functions
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def test_ndarray_full():
core: Fix Literal use in variable type annotation
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n_float: ndarray[float, 1] = np_full([1], 2.0)
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_float_1(n_float)
core: Fix Literal use in variable type annotation
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n_i32: ndarray[int32, 1] = np_full([1], 2)
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_int32_1(n_i32)
core: Implement most ndarray-creation functions
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def test_ndarray_eye():
core: Fix Literal use in variable type annotation
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n: ndarray[float, 2] = np_eye(2)
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_float_2(n)
core: Implement most ndarray-creation functions
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def test_ndarray_identity():
core: Fix Literal use in variable type annotation
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n: ndarray[float, 2] = np_identity(2)
core: Implement elementwise binary operators Including immediate variants of these operators.
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output_ndarray_float_2(n)
core: Implement most ndarray-creation functions
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core: Implement `ndarray.fill`
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def test_ndarray_fill():
n: ndarray[float, 2] = np_empty([2, 2])
n.fill(1.0)
core: Implement elementwise binary operators Including immediate variants of these operators.
2024-03-13 11:16:23 +08:00
output_ndarray_float_2(n)
core: Implement `ndarray.fill`
2024-03-06 16:53:41 +08:00
standalone: Update ndarray.py to output all elements in ndarrays
2024-03-07 13:08:45 +08:00
def test_ndarray_copy():
x: ndarray[float, 2] = np_identity(2)
y = x.copy()
x.fill(0.0)
core: Implement elementwise binary operators Including immediate variants of these operators.
2024-03-13 11:16:23 +08:00
output_ndarray_float_2(x)
output_ndarray_float_2(y)
core/expr: Implement negative indices for ndarray
2024-04-15 12:20:13 +08:00
def test_ndarray_neg_idx():
x = np_identity(2)
for i in range(-1, -3, -1):
for j in range(-1, -3, -1):
output_float64(x[i][j])
core: Implement elementwise binary operators Including immediate variants of these operators.
2024-03-13 11:16:23 +08:00
def test_ndarray_add():
x = np_identity(2)
y = x + np_ones([2, 2])
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_add_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_add_broadcast_lhs_scalar():
x = np_identity(2)
# y: ndarray[float, 2] = 1.0 + x
y = 1.0 + x
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_add_broadcast_rhs_scalar():
x = np_identity(2)
# y: ndarray[float, 2] = x + 1.0
y = x + 1.0
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_iadd():
x = np_identity(2)
x += np_ones([2, 2])
output_ndarray_float_2(x)
def test_ndarray_iadd_broadcast():
x = np_identity(2)
x += np_ones([2])
output_ndarray_float_2(x)
def test_ndarray_iadd_broadcast_scalar():
x = np_identity(2)
x += 1.0
output_ndarray_float_2(x)
def test_ndarray_sub():
x = np_ones([2, 2])
y = x - np_identity(2)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_sub_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_sub_broadcast_lhs_scalar():
x = np_identity(2)
# y: ndarray[float, 2] = 1.0 - x
y = 1.0 - x
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_sub_broadcast_rhs_scalar():
x = np_identity(2)
# y: ndarray[float, 2] = x - 1
y = x - 1.0
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_isub():
x = np_ones([2, 2])
x -= np_identity(2)
output_ndarray_float_2(x)
def test_ndarray_isub_broadcast():
x = np_identity(2)
x -= np_ones([2])
output_ndarray_float_2(x)
def test_ndarray_isub_broadcast_scalar():
x = np_identity(2)
x -= 1.0
output_ndarray_float_2(x)
def test_ndarray_mul():
x = np_ones([2, 2])
y = x * np_identity(2)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_mul_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_mul_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_mul_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_imul():
x = np_ones([2, 2])
x *= np_identity(2)
output_ndarray_float_2(x)
def test_ndarray_imul_broadcast():
x = np_identity(2)
x *= np_ones([2])
output_ndarray_float_2(x)
def test_ndarray_imul_broadcast_scalar():
x = np_identity(2)
x *= 2.0
output_ndarray_float_2(x)
def test_ndarray_truediv():
x = np_identity(2)
y = x / np_ones([2, 2])
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_truediv_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_truediv_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_truediv_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_itruediv():
x = np_identity(2)
x /= np_ones([2, 2])
output_ndarray_float_2(x)
def test_ndarray_itruediv_broadcast():
x = np_identity(2)
x /= np_ones([2])
output_ndarray_float_2(x)
def test_ndarray_itruediv_broadcast_scalar():
x = np_identity(2)
x /= 2.0
output_ndarray_float_2(x)
def test_ndarray_floordiv():
x = np_identity(2)
y = x // np_ones([2, 2])
output_ndarray_float_2(x)
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
standalone: Update ndarray.py to output all elements in ndarrays
2024-03-07 13:08:45 +08:00
core: Implement elementwise binary operators Including immediate variants of these operators.
2024-03-13 11:16:23 +08:00
output_ndarray_float_2(x)
standalone: Update ndarray.py to output all elements in ndarrays
2024-03-07 13:08:45 +08:00
core: Implement elementwise unary operators
2024-03-27 17:06:58 +08:00
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)
core: Fix __inv__ for i8-based boolean operands
2024-04-12 15:35:36 +08:00
x_bool = np_full([2, 2], True)
y_bool = ~x_bool
output_ndarray_bool_2(x_bool)
output_ndarray_bool_2(y_bool)
core: Implement elementwise comparison operators
2024-03-27 12:57:11 +08:00
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)
core: Implement ndarray constructor and numpy.empty
2023-11-17 17:30:27 +08:00
def run() -> int32:
test_ndarray_ctor()
test_ndarray_empty()
core: Implement most ndarray-creation functions
2023-11-27 13:25:53 +08:00
test_ndarray_zeros()
test_ndarray_ones()
test_ndarray_full()
test_ndarray_eye()
test_ndarray_identity()
core: Implement `ndarray.fill`
2024-03-06 16:53:41 +08:00
test_ndarray_fill()
standalone: Update ndarray.py to output all elements in ndarrays
2024-03-07 13:08:45 +08:00
test_ndarray_copy()
core/expr: Implement negative indices for ndarray
2024-04-15 12:20:13 +08:00
test_ndarray_neg_idx()
core: Implement elementwise binary operators Including immediate variants of these operators.
2024-03-13 11:16:23 +08:00
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()
core: Implement elementwise unary operators
2024-03-27 17:06:58 +08:00
test_ndarray_pos()
test_ndarray_neg()
test_ndarray_inv()
core: Implement elementwise comparison operators
2024-03-27 12:57:11 +08:00
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()
core: Implement ndarray constructor and numpy.empty
2023-11-17 17:30:27 +08:00
return 0