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[UnitTests] Added cuDNN to default test targets #8383

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merged 5 commits into from
Aug 9, 2021

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Lunderberg
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@Lunderberg Lunderberg commented Jul 1, 2021

Some unit tests explicitly test cudnn in addition to tvm.testing.enabled_targets(). This moved the cudnn checks into the same framework as all other targets, and adds it to the default list of targets to be run. Also, added @tvm.testing.requires_cudnn for tests specific to cudnn.

In principle, this should pass CI, since any non-cudnn tests can fall back to the cuda implementation, but "should" is a bit of a magic word.

@Lunderberg Lunderberg force-pushed the tvm_testing_default_targets branch from 04a36d4 to 1a2838e Compare July 8, 2021 16:13
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Updated to fix pylint error.

@Lunderberg Lunderberg force-pushed the tvm_testing_default_targets branch 2 times, most recently from b6fb4d9 to f57debb Compare July 12, 2021 16:14
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Current failures.

  • test_conv2d_nchw doesn't support asymmetric padding on cudnn. Can add an explicit pytest.xfail on that test case once [Topi][UnitTests] Parameterize conv2d and depthwise_conv2d tests #8433 is merged.
  • test_batch_matmul errors out for dynamic batch matmul not being supported on cuda. Changed check from direct comparison with the string "cuda" to a check on the target.kind.name.

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It would be better to also let a Vulkan folk review the changes in target_kind.cc.

Comment on lines 383 to 384
if len(target_names) == 0:
target_names = DEFAULT_TEST_TARGETS
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nit

Suggested change
if len(target_names) == 0:
target_names = DEFAULT_TEST_TARGETS
if not target_names:
target_names = DEFAULT_TEST_TARGETS

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Good call, and updated.

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Will need rebasing on main to resolve conflicts with #8602 (merged) and #8542 (waiting on CI). #8542 is the more important one, so this PR can wait until it is done.

…arget

- Read target.kind.name instead of using string manipulation.

- Target device query on a non-existent target is no longer an error.
  This occurs if expanding `vulkan -from_device=0` on a non-GPU
  machine.
Some unit tests explicitly test cudnn in addition to
`tvm.testing.enabled_targets()`.  This moved the cudnn checks into the
same framework as all other targets, and adds it to the default list
of targets to be run.  Also, added `@tvm.testing.requires_cudnn` for
tests specific to cudnn.
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Hopefully the last update needed here, rebased to main and fixed an issue with the conv2d_cudnn handling of dilation.

Previously, cuda/nvptx targets were excluded.  Changed it to look up
by target.kind.name, and to also exclude vulkan/opencl, as the dynamic
lookup currently doesn't work on those backends.
@masahi masahi merged commit 8679b4f into apache:main Aug 9, 2021
@Lunderberg Lunderberg deleted the tvm_testing_default_targets branch August 9, 2021 01:19
mehrdadh pushed a commit to mehrdadh/tvm that referenced this pull request Aug 11, 2021
* [Target][UnitTests] Look up target requirements based on tvm.target.Target

- Read target.kind.name instead of using string manipulation.

- Target device query on a non-existent target is no longer an error.
  This occurs if expanding `vulkan -from_device=0` on a non-GPU
  machine.

* [UnitTests] Added cuDNN target to default test targets

Some unit tests explicitly test cudnn in addition to
`tvm.testing.enabled_targets()`.  This moved the cudnn checks into the
same framework as all other targets, and adds it to the default list
of targets to be run.  Also, added `@tvm.testing.requires_cudnn` for
tests specific to cudnn.

* [UnitTests] pytest.xfail for CuDNN conv2d with asymmetric padding

* [Topi][CuDNN] Added handling of dilation to conv2d_cudnn

* [Topi] Skip dynamic batch matmul on cudnn, vulkan, opencl

Previously, cuda/nvptx targets were excluded.  Changed it to look up
by target.kind.name, and to also exclude vulkan/opencl, as the dynamic
lookup currently doesn't work on those backends.

Co-authored-by: Eric Lunderberg <[email protected]>
ylc pushed a commit to ylc/tvm that referenced this pull request Sep 29, 2021
* [Target][UnitTests] Look up target requirements based on tvm.target.Target

- Read target.kind.name instead of using string manipulation.

- Target device query on a non-existent target is no longer an error.
  This occurs if expanding `vulkan -from_device=0` on a non-GPU
  machine.

* [UnitTests] Added cuDNN target to default test targets

Some unit tests explicitly test cudnn in addition to
`tvm.testing.enabled_targets()`.  This moved the cudnn checks into the
same framework as all other targets, and adds it to the default list
of targets to be run.  Also, added `@tvm.testing.requires_cudnn` for
tests specific to cudnn.

* [UnitTests] pytest.xfail for CuDNN conv2d with asymmetric padding

* [Topi][CuDNN] Added handling of dilation to conv2d_cudnn

* [Topi] Skip dynamic batch matmul on cudnn, vulkan, opencl

Previously, cuda/nvptx targets were excluded.  Changed it to look up
by target.kind.name, and to also exclude vulkan/opencl, as the dynamic
lookup currently doesn't work on those backends.

Co-authored-by: Eric Lunderberg <[email protected]>
ylc pushed a commit to ylc/tvm that referenced this pull request Jan 13, 2022
* [Target][UnitTests] Look up target requirements based on tvm.target.Target

- Read target.kind.name instead of using string manipulation.

- Target device query on a non-existent target is no longer an error.
  This occurs if expanding `vulkan -from_device=0` on a non-GPU
  machine.

* [UnitTests] Added cuDNN target to default test targets

Some unit tests explicitly test cudnn in addition to
`tvm.testing.enabled_targets()`.  This moved the cudnn checks into the
same framework as all other targets, and adds it to the default list
of targets to be run.  Also, added `@tvm.testing.requires_cudnn` for
tests specific to cudnn.

* [UnitTests] pytest.xfail for CuDNN conv2d with asymmetric padding

* [Topi][CuDNN] Added handling of dilation to conv2d_cudnn

* [Topi] Skip dynamic batch matmul on cudnn, vulkan, opencl

Previously, cuda/nvptx targets were excluded.  Changed it to look up
by target.kind.name, and to also exclude vulkan/opencl, as the dynamic
lookup currently doesn't work on those backends.

Co-authored-by: Eric Lunderberg <[email protected]>
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3 participants