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Merged
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May 2, 2024
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Changes test_func_order tests for some unary functions #1658

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13 changes: 7 additions & 6 deletions dpctl/tests/elementwise/test_abs.py
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Expand Up @@ -84,18 +84,19 @@ def test_abs_order(dtype):
skip_if_dtype_not_supported(dtype, q)

arg_dt = np.dtype(dtype)
exp_dt = np.abs(np.ones(tuple(), dtype=arg_dt)).dtype
input_shape = (10, 10, 10, 10)
X = dpt.empty(input_shape, dtype=arg_dt, sycl_queue=q)
X[..., 0::2] = 1
X[..., 1::2] = 0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.ones(U.shape, dtype=exp_dt)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
for ord in ["C", "F", "A", "K"]:
Y = dpt.abs(U, order=ord)
expected_Y = np.ones(Y.shape, dtype=Y.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
assert np.allclose(dpt.asnumpy(Y), expected_Y)


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2 changes: 1 addition & 1 deletion dpctl/tests/elementwise/test_complex.py
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Expand Up @@ -120,7 +120,7 @@ def test_complex_order(np_call, dpt_call, dtype):
expected_Y = np_call(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt_call(U, order=ord)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
assert_allclose(dpt.asnumpy(Y), expected_Y)


@pytest.mark.parametrize("dtype", ["c8", "c16"])
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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_exp2.py
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Expand Up @@ -103,11 +103,11 @@ def test_exp2_order(dtype):
X[..., 0::2] = 1 / 4
X[..., 1::2] = 1 / 2

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.exp2(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.exp2(U, order=ord)
expected_Y = np.exp2(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_expm1.py
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Expand Up @@ -103,11 +103,11 @@ def test_expm1_order(dtype):
X[..., 0::2] = 1 / 50
X[..., 1::2] = 1 / 25

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.expm1(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.expm1(U, order=ord)
expected_Y = np.expm1(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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11 changes: 6 additions & 5 deletions dpctl/tests/elementwise/test_isfinite.py
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Expand Up @@ -18,6 +18,7 @@

import numpy as np
import pytest
from numpy.testing import assert_allclose

import dpctl.tensor as dpt
from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
Expand Down Expand Up @@ -90,9 +91,9 @@ def test_isfinite_order(dtype):
input_shape = (10, 10, 10, 10)
X = dpt.ones(input_shape, dtype=arg_dt, sycl_queue=q)

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
expected_Y = np.full(U.shape, fill_value=True, dtype=dpt.bool)
for ord in ["C", "F", "A", "K"]:
Y = dpt.isfinite(U, order=ord)
expected_Y = np.full(Y.shape, True, dtype=Y.dtype)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
assert_allclose(dpt.asnumpy(Y), expected_Y)
11 changes: 6 additions & 5 deletions dpctl/tests/elementwise/test_isinf.py
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Expand Up @@ -18,6 +18,7 @@

import numpy as np
import pytest
from numpy.testing import assert_allclose

import dpctl.tensor as dpt
from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
Expand Down Expand Up @@ -84,9 +85,9 @@ def test_isinf_order(dtype):
input_shape = (10, 10, 10, 10)
X = dpt.ones(input_shape, dtype=arg_dt, sycl_queue=q)

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
expected_Y = np.full(U.shape, fill_value=False, dtype=dpt.bool)
for ord in ["C", "F", "A", "K"]:
Y = dpt.isinf(U, order=ord)
expected_Y = np.full(Y.shape, False, dtype=Y.dtype)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
assert_allclose(dpt.asnumpy(Y), expected_Y)
8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_isnan.py
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Expand Up @@ -90,9 +90,9 @@ def test_isnan_order(dtype):
input_shape = (10, 10, 10, 10)
X = dpt.ones(input_shape, dtype=arg_dt, sycl_queue=q)

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[::2, ::-1, ::-1, ::5], perms)
expected_Y = np.full(U.shape, fill_value=False, dtype=dpt.bool)
for ord in ["C", "F", "A", "K"]:
Y = dpt.isnan(U, order=ord)
expected_Y = np.full(Y.shape, False, dtype=Y.dtype)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_log.py
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Expand Up @@ -103,11 +103,11 @@ def test_log_order(dtype):
X[..., 0::2] = 4 * dpt.e
X[..., 1::2] = 10 * dpt.e

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.log(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.log(U, order=ord)
expected_Y = np.log(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_log10.py
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Expand Up @@ -107,11 +107,11 @@ def test_log_order(dtype):
X[..., 0::2] = 4 * dpt.e
X[..., 1::2] = 10 * dpt.e

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.log10(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.log10(U, order=ord)
expected_Y = np.log10(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_log1p.py
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Expand Up @@ -103,11 +103,11 @@ def test_log1p_order(dtype):
X[..., 0::2] = dpt.e / 1000
X[..., 1::2] = dpt.e / 100

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.log1p(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.log1p(U, order=ord)
expected_Y = np.log1p(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_log2.py
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Expand Up @@ -103,11 +103,11 @@ def test_log_order(dtype):
X[..., 0::2] = 4 * dpt.e
X[..., 1::2] = 10 * dpt.e

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.log2(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.log2(U, order=ord)
expected_Y = np.log2(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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12 changes: 6 additions & 6 deletions dpctl/tests/elementwise/test_negative.py
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Expand Up @@ -76,11 +76,11 @@ def test_negative_order(dtype):
X[..., 0::2] = 1
X[..., 1::2] = 0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.negative(np.ones(U.shape, dtype=U.dtype))
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
for ord in ["C", "F", "A", "K"]:
Y = dpt.negative(U, order=ord)
expected_Y = np.negative(np.ones(Y.shape, dtype=Y.dtype))
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
12 changes: 6 additions & 6 deletions dpctl/tests/elementwise/test_positive.py
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Expand Up @@ -69,11 +69,11 @@ def test_positive_order(dtype):
X[..., 0::2] = 1
X[..., 1::2] = 0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.ones(U.shape, dtype=U.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
for ord in ["C", "F", "A", "K"]:
Y = dpt.positive(U, order=ord)
expected_Y = np.ones(Y.shape, dtype=Y.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
assert np.allclose(dpt.asnumpy(Y), expected_Y)
13 changes: 7 additions & 6 deletions dpctl/tests/elementwise/test_sign.py
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Expand Up @@ -64,18 +64,19 @@ def test_sign_order(dtype):
skip_if_dtype_not_supported(dtype, q)

arg_dt = np.dtype(dtype)
expected_dt = np.sign(np.ones(tuple(), dtype=arg_dt)).dtype
input_shape = (10, 10, 10, 10)
X = dpt.empty(input_shape, dtype=arg_dt, sycl_queue=q)
X[..., 0::2] = 1
X[..., 1::2] = 0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.ones(U.shape, dtype=expected_dt)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
for ord in ["C", "F", "A", "K"]:
Y = dpt.sign(U, order=ord)
expected_Y = np.ones(Y.shape, dtype=Y.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
assert np.allclose(dpt.asnumpy(Y), expected_Y)


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8 changes: 4 additions & 4 deletions dpctl/tests/elementwise/test_sqrt.py
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Expand Up @@ -110,11 +110,11 @@ def test_sqrt_order(dtype):
X[..., 0::2] = 16.0
X[..., 1::2] = 23.0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.sqrt(dpt.asnumpy(U))
for ord in ["C", "F", "A", "K"]:
Y = dpt.sqrt(U, order=ord)
expected_Y = np.sqrt(dpt.asnumpy(U))
tol = 8 * max(
dpt.finfo(Y.dtype).resolution,
np.finfo(expected_Y.dtype).resolution,
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12 changes: 6 additions & 6 deletions dpctl/tests/elementwise/test_square.py
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Expand Up @@ -69,13 +69,13 @@ def test_square_order(dtype):
X[..., 0::2] = 2
X[..., 1::2] = 0

for ord in ["C", "F", "A", "K"]:
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
for perms in itertools.permutations(range(4)):
U = dpt.permute_dims(X[:, ::-1, ::-1, :], perms)
expected_Y = np.full(U.shape, 4, dtype=U.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
for ord in ["C", "F", "A", "K"]:
Y = dpt.square(U, order=ord)
expected_Y = np.full(Y.shape, 4, dtype=Y.dtype)
expected_Y[..., 1::2] = 0
expected_Y = np.transpose(expected_Y, perms)
assert np.allclose(dpt.asnumpy(Y), expected_Y)


Expand Down