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antonwolfyantonwolfy
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Leave only dot tests
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-67
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3 files changed

+71
-67
lines changed

‎conda-recipe/meta.yaml‎

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@@ -50,6 +50,7 @@ build:
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test:
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requires:
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- pytest
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- pytest-repeat
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- setuptools
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about:

‎conda-recipe/run_test.bat‎

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@@ -45,6 +45,9 @@ if %errorlevel% neq 0 exit 1
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"%PYTHON%" -m pytest -ra --pyargs dpnp.tests.test_ndarray
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if %errorlevel% neq 0 exit 1
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"%PYTHON%" -m pytest --count 100 -ra -v --pyargs dpnp.tests.test_usm_type::test_2in_1out
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if %errorlevel% neq 0 exit 1
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"%PYTHON%" -m pytest -ra -v --pyargs dpnp.tests.test_usm_type
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if %errorlevel% neq 0 exit 1
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‎dpnp/tests/test_usm_type.py‎

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@@ -684,78 +684,78 @@ def test_1in_1out(func, data, usm_type):
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@pytest.mark.parametrize(
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"func,data1,data2",
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[
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pytest.param(
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"allclose",
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[[1.2, -0.0], [-7, 2.34567]],
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[[1.2, 0.0], [-7, 2.34567]],
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),
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pytest.param("append", [1, 2, 3], [4, 5, 6]),
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pytest.param("arctan2", [-1, +1, +1, -1], [-1, -1, +1, +1]),
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pytest.param("compress", [False, True, True], [0, 1, 2, 3, 4]),
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pytest.param("copysign", [0.0, 1.0, 2.0], [-1.0, 0.0, 1.0]),
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pytest.param("cross", [1.0, 2.0, 3.0], [4.0, 5.0, 6.0]),
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pytest.param("digitize", [0.2, 6.4, 3.0], [0.0, 1.0, 2.5, 4.0]),
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pytest.param(
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"corrcoef",
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[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]],
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[[0.7, 0.8, 0.9], [1.0, 1.1, 1.2]],
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),
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pytest.param("correlate", [1, 2, 3], [0, 1, 0.5]),
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# pytest.param(
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# "allclose",
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# [[1.2, -0.0], [-7, 2.34567]],
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# [[1.2, 0.0], [-7, 2.34567]],
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# ),
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# pytest.param("append", [1, 2, 3], [4, 5, 6]),
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# pytest.param("arctan2", [-1, +1, +1, -1], [-1, -1, +1, +1]),
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# pytest.param("compress", [False, True, True], [0, 1, 2, 3, 4]),
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# pytest.param("copysign", [0.0, 1.0, 2.0], [-1.0, 0.0, 1.0]),
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# pytest.param("cross", [1.0, 2.0, 3.0], [4.0, 5.0, 6.0]),
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# pytest.param("digitize", [0.2, 6.4, 3.0], [0.0, 1.0, 2.5, 4.0]),
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# pytest.param(
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# "corrcoef",
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# [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]],
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# [[0.7, 0.8, 0.9], [1.0, 1.1, 1.2]],
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# ),
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# pytest.param("correlate", [1, 2, 3], [0, 1, 0.5]),
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# dpnp.dot has 3 different implementations based on input arrays dtype
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# checking all of them
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pytest.param("dot", [3.0, 4.0, 5.0], [1.0, 2.0, 3.0]),
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pytest.param("dot", [3, 4, 5], [1, 2, 3]),
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pytest.param("dot", [3 + 2j, 4 + 1j, 5], [1, 2 + 3j, 3]),
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pytest.param("extract", [False, True, True, False], [0, 1, 2, 3]),
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pytest.param(
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"float_power",
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[0, 1, 2, 3, 4, 5],
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[1.0, 2.0, 3.0, 3.0, 2.0, 1.0],
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),
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pytest.param("fmax", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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pytest.param("fmin", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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pytest.param("fmod", [5, 3], [2, 2.0]),
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pytest.param(
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"gcd",
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[0, 1, 2, 3, 4, 5],
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[20, 20, 20, 20, 20, 20],
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),
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pytest.param(
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"gradient", [1, 2, 4, 7, 11, 16], [0.0, 1.0, 1.5, 3.5, 4.0, 6.0]
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),
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pytest.param("heaviside", [-1.5, 0, 2.0], [1]),
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pytest.param(
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"hypot", [[1.0, 2.0, 3.0, 4.0]], [[-1.0, -2.0, -4.0, -5.0]]
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),
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pytest.param("inner", [1.0, 2.0, 3.0], [4.0, 5.0, 6.0]),
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pytest.param("kron", [3.0, 4.0, 5.0], [1.0, 2.0]),
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pytest.param(
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"lcm",
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[0, 1, 2, 3, 4, 5],
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[20, 20, 20, 20, 20, 20],
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),
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pytest.param(
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"ldexp",
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[5, 5, 5, 5, 5],
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[0, 1, 2, 3, 4],
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),
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pytest.param("logaddexp", [[-1, 2, 5, 9]], [[4, -3, 2, -8]]),
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pytest.param("logaddexp2", [[-1, 2, 5, 9]], [[4, -3, 2, -8]]),
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pytest.param("maximum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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pytest.param("minimum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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pytest.param("nextafter", [1, 2], [2, 1]),
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pytest.param("searchsorted", [11, 12, 13, 14, 15], [-10, 20, 12, 13]),
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pytest.param(
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"tensordot",
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[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]],
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[[4.0, 4.0, 4.0], [4.0, 4.0, 4.0]],
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),
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pytest.param("trapezoid", [1, 2, 3], [4, 6, 8]),
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# dpnp.vdot has 3 different implementations based on input arrays dtype
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# checking all of them
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pytest.param("vdot", [3.0, 4.0, 5.0], [1.0, 2.0, 3.0]),
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pytest.param("vdot", [3, 4, 5], [1, 2, 3]),
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pytest.param("vdot", [3 + 2j, 4 + 1j, 5], [1, 2 + 3j, 3]),
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# pytest.param("extract", [False, True, True, False], [0, 1, 2, 3]),
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# pytest.param(
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# "float_power",
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# [0, 1, 2, 3, 4, 5],
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# [1.0, 2.0, 3.0, 3.0, 2.0, 1.0],
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# ),
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# pytest.param("fmax", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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# pytest.param("fmin", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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# pytest.param("fmod", [5, 3], [2, 2.0]),
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# pytest.param(
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# "gcd",
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# [0, 1, 2, 3, 4, 5],
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# [20, 20, 20, 20, 20, 20],
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# ),
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# pytest.param(
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# "gradient", [1, 2, 4, 7, 11, 16], [0.0, 1.0, 1.5, 3.5, 4.0, 6.0]
725+
# ),
726+
# pytest.param("heaviside", [-1.5, 0, 2.0], [1]),
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# pytest.param(
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# "hypot", [[1.0, 2.0, 3.0, 4.0]], [[-1.0, -2.0, -4.0, -5.0]]
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# ),
730+
# pytest.param("inner", [1.0, 2.0, 3.0], [4.0, 5.0, 6.0]),
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# pytest.param("kron", [3.0, 4.0, 5.0], [1.0, 2.0]),
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# pytest.param(
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# "lcm",
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# [0, 1, 2, 3, 4, 5],
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# [20, 20, 20, 20, 20, 20],
736+
# ),
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# pytest.param(
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# "ldexp",
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# [5, 5, 5, 5, 5],
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# [0, 1, 2, 3, 4],
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# ),
742+
# pytest.param("logaddexp", [[-1, 2, 5, 9]], [[4, -3, 2, -8]]),
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# pytest.param("logaddexp2", [[-1, 2, 5, 9]], [[4, -3, 2, -8]]),
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# pytest.param("maximum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
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# pytest.param("minimum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
746+
# pytest.param("nextafter", [1, 2], [2, 1]),
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# pytest.param("searchsorted", [11, 12, 13, 14, 15], [-10, 20, 12, 13]),
748+
# pytest.param(
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# "tensordot",
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# [[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]],
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# [[4.0, 4.0, 4.0], [4.0, 4.0, 4.0]],
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# ),
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# pytest.param("trapezoid", [1, 2, 3], [4, 6, 8]),
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# # dpnp.vdot has 3 different implementations based on input arrays dtype
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# # checking all of them
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# pytest.param("vdot", [3.0, 4.0, 5.0], [1.0, 2.0, 3.0]),
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# pytest.param("vdot", [3, 4, 5], [1, 2, 3]),
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# pytest.param("vdot", [3 + 2j, 4 + 1j, 5], [1, 2 + 3j, 3]),
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],
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)
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@pytest.mark.parametrize("usm_type_x", list_of_usm_types, ids=list_of_usm_types)

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