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Apply fallback to numpy for all unsupported functions on cuda devices. #2075
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View rendered docs @ https://intelpython.github.io/dpnp/pull/2075/index.html |
Returns | ||
------- | ||
out : bool | ||
Return ``True`` if object has a cuda backend, otherwise``False``. |
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Return ``True`` if object has a cuda backend, otherwise``False``. | |
Return ``True`` if object has a CUDA backend, otherwise ``False``. |
@@ -11,24 +11,18 @@ | |||
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def _gen_array(dtype, alloc_q=None): |
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def _gen_array(dtype, alloc_q=None): | |
# TODO: to roll back the changes once the issue with CUDA support is resolved for random | |
def _gen_array(dtype, alloc_q=None): |
@@ -11,6 +11,7 @@ | |||
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@pytest.mark.usefixtures("allow_fall_back_on_numpy") |
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dpnp.median
has been implemented in #2117
@pytest.mark.usefixtures("allow_fall_back_on_numpy") |
Apply fallback to numpy for all unsupported functions on CUDA devices.
Added tests/skipped_tests_cuda.tbl