integration TestDynUNetWithInstanceNorm3dNVFuser
See original GitHub issueDescribe the bug logs using pytorch image 22.04 https://github.com/Project-MONAI/MONAI/runs/6306011370?check_suite_focus=true
(| NVIDIA-SMI 495.29.05 Driver Version: 495.29.05 CUDA Version: 11.5 )
ERROR: test_consistency_0 (tests.test_dynunet.TestDynUNetWithInstanceNorm3dNVFuser)
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Traceback (most recent call last):
File "/opt/conda/lib/python3.8/site-packages/parameterized/parameterized.py", line 533, in standalone_func
test_compute_0 (tests.test_prepare_batch_default_dist.DistributedPrepareBatchDefault) (10.5s)
test_compute_1 (tests.test_prepare_batch_default_dist.DistributedPrepareBatchDefault) (10.6s)
test_verify_0__tmp_tmp_HuvzKkaSgJ_tests_testing_data_metadata_json (tests.test_bundle_verify_net.TestVerifyNetwork) (11.2s)
return func(*(a + p.args), **p.kwargs)
File "/tmp/tmp.HuvzKkaSgJ/tests/test_dynunet.py", line 146, in test_consistency
result_fuser = net_fuser(input_tensor)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/monai/networks/nets/dynunet.py", line 268, in forward
out = self.skip_layers(x)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/monai/networks/nets/dynunet.py", line 46, in forward
downout = self.downsample(x)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/monai/networks/blocks/dynunet_block.py", line 80, in forward
out = self.norm1(out)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/apex/normalization/instance_norm.py", line 138, in forward
out = InstanceNormNVFuserFunction.apply(
File "/opt/conda/lib/python3.8/site-packages/apex/normalization/instance_norm.py", line 16, in forward
instance_norm_nvfuser_cuda = importlib.import_module("instance_norm_nvfuser_cuda")
File "/opt/conda/lib/python3.8/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
File "<frozen importlib._bootstrap>", line 991, in _find_and_load
File "<frozen importlib._bootstrap>", line 975, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 657, in _load_unlocked
File "<frozen importlib._bootstrap>", line 556, in module_from_spec
File "<frozen importlib._bootstrap_external>", line 1166, in create_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
ImportError: /opt/conda/lib/python3.8/site-packages/instance_norm_nvfuser_cuda.cpython-38-x86_64-linux-gnu.so: undefined symbol: _ZTVN5torch3jit5fuser4cuda3kir6KernelE
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Issue Analytics
- State:
- Created a year ago
- Comments:6 (5 by maintainers)
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Top GitHub Comments
thanks for looking into this, now it’s clear that reinstalling pytorch/torchvision in the docker breaks the apex customized module https://github.com/Project-MONAI/MONAI/blob/557c12940e3e31be3f01f8031afcd6c027a8870d/.github/workflows/cron.yml#L134 https://github.com/Project-MONAI/MONAI/blob/557c12940e3e31be3f01f8031afcd6c027a8870d/.github/workflows/cron.yml#L149 and Yiheng’s PR makes the call robust in this case https://github.com/Project-MONAI/MONAI/pull/4241
Updates: I checked more about this issue, and with Peixin’s help, we found that it may not the cuda/driver/torch version/docker issue, same environment is used for the
cron-docker
test (https://github.com/Project-MONAI/MONAI/runs/6306012243?check_suite_focus=true) and the docker image is based on 22.04. So far, the issue is avoided by adding more checks, but I’m not sure if there is any other issue within the env building part ofcron-pip
.