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[inductor][CI] also skip rexnet_100 on non-dynamic shapes (#96691)

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Recent failures show rexnet_100 accuracy is flaky also on non-dynamic shapes (was already disabled for dynamic shapes in #96474). The failure occurs for the same reason (stem.bn.weight.grad).
e.g. https://github.com/pytorch/pytorch/actions/runs/4402868441/jobs/7710977874

Pull Request resolved: https://github.com/pytorch/pytorch/pull/96691
Approved by: https://github.com/desertfire
This commit is contained in:
David Berard 2023-03-13 15:46:15 -07:00 committed by PyTorch MergeBot
parent a916d64900
commit 6e3d51b08a
1 changed files with 1 additions and 1 deletions
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benchmarks/dynamo/common.py
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@ -201,6 +201,7 @@ CI_SKIP[CI("inductor", training=True)] = [
"fbnetv3_b", # accuracy
"levit_128", # fp64_OOM
# https://github.com/pytorch/pytorch/issues/94066
"rexnet_100", # Accuracy failed for key name stem.bn.weight.grad
"sebotnet33ts_256", # Accuracy failed for key name stem.conv1.conv.weight.grad
"xcit_large_24_p8_224", # fp64_OOM
]
@ -245,7 +246,6 @@ CI_SKIP[CI("inductor", training=True, dynamic=True)] = [
# timm_models
"eca_botnext26ts_256", # 'float' object has no attribute '_has_symbolic_sizes_strides'
"mixnet_l", # 'float' object has no attribute '_has_symbolic_sizes_strides'
"rexnet_100", # Accuracy failed for key name stem.bn.weight.grad
"tf_efficientnet_b0", # 'float' object has no attribute '_has_symbolic_sizes_strides'
"tf_mixnet_l", # 'float' object has no attribute '_has_symbolic_sizes_strides'
"visformer_small", # 'float' object has no attribute '_has_symbolic_sizes_strides'