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Enable CUDA EP unit testing on Windows #20039
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Fix cuda_test_provider gtest argument stack corruption
yuslepukhin
requested review from
snnn,
chenfucn,
pranavsharma,
HectorSVC and
wangyems
March 23, 2024 00:25
snnn
previously approved these changes
Mar 25, 2024
snnn
previously approved these changes
Mar 25, 2024
pranavsharma
previously approved these changes
Mar 25, 2024
onnxruntime/core/util/matrix_layout.h:381:14: error: unused parameter ‘magic’ [-Werror=unused-parameter] |
snnn
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Mar 27, 2024
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Thank you!
TedThemistokleous
pushed a commit
to TedThemistokleous/onnxruntime
that referenced
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May 7, 2024
### Description Address build issues and source code discrepancies. Fix cuda_test_provider gtest argument stack corruption. ### Motivation and Context `OpTester` class that is widely used for kernel testing is not suitable for testing internal classes for EPs that are built as shared objects. Currently, CUDA EP tests run only on Linux. We want to enable testing and developments on Windows, and create a usable pattern for testing of other EPs internals. Alternatives considered: Abstracting EP unit tests into separate test executable such as `onnxruntime_test_all`. This alternative was rejected as it would create a lot more changes in the established patterns, and potentially interfere with CUDA functionality with more complex source code maintanence.
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Description
Address build issues and source code discrepancies.
Fix cuda_test_provider gtest argument stack corruption.
Motivation and Context
OpTester
class that is widely used for kernel testing is notsuitable for testing internal classes for EPs that are built as shared objects.
Currently, CUDA EP tests run only on Linux.
We want to enable testing and developments on Windows,
and create a usable pattern for testing of other EPs internals.
Alternatives considered:
Abstracting EP unit tests into separate test executable such as
onnxruntime_test_all
.This alternative was rejected as it would create a lot more changes in the established patterns,
and potentially interfere with CUDA functionality with more complex source code maintanence.