[tests] fix broken xformers tests #9206
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| key = attn.head_to_batch_dim(key).contiguous() | ||
| value = attn.head_to_batch_dim(value).contiguous() | ||
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| if attn.norm_q is not None: |
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Which test is this meant to fix?
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The CogVideoX tests. This was needed because we added QK norm in Attn2.0 and FusedAttn2.0.
However, after the new CogVideoX-5B PR, I think we can no longer support XFormers due to needing a custom attention processor. Maybe we can skip the test here because otherwise we'd need a custom XFormers processor variant for it?
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| if test_mean_pixel_difference: | ||
| assert_mean_pixel_difference(output_with_offload[0], output_without_offload[0]) | ||
| if torch.is_tensor(output_without_offload): |
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If the issue is the output shapes it would be better to redefine the tests for that output shape inside the pipeline test modules. Similar to what's done here:
* fix xformers tests * remove unnecessary modifications to cogvideox tests * update
* fix xformers tests * remove unnecessary modifications to cogvideox tests * update
What does this PR do?
Context: https://github.com/huggingface/diffusers/actions/runs/10414785958/job/28844261331#logs
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@DN6