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[PyTorch] Deprecate grouped linear and MLP environment gates - #3584
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LGTM. Thanks for cleaning these env variables. All @timmoon10's comments seem to be resolved as well. @zhongbozhu I resolved the merge conflicts. |
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| """Whether this fused operation is supported on the current system.""" | ||
| if int(os.environ.get("NVTE_CUTEDSL_FUSED_GROUPED_MLP", "0")) <= 0: | ||
| return False | ||
| if get_device_compute_capability()[0] != 10: |
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CUDA-free support checks raise If CUDA is unavailable,
is_supported() now calls get_device_compute_capability() instead of returning False. That helper calls torch.cuda.current_device(), so the support check raises rather than letting the caller use the unfused path. The unary-fusion callback can hit this check while building a plan, before checking whether the recipe or operations are candidates for fusion.
Knowledge Base Used: PyTorch tensor and operator abstractions
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Signed-off-by: zhongboz <zhongboz@nvidia.com>
Signed-off-by: zhongboz <zhongboz@nvidia.com>
Signed-off-by: Zhongbo Zhu <zhongboz@nvidia.com>
Signed-off-by: zhongboz <zhongboz@nvidia.com>
Signed-off-by: zhongboz <zhongboz@nvidia.com>
Signed-off-by: zhongboz <zhongboz@nvidia.com>
Signed-off-by: zhongboz <zhongboz@nvidia.com>
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Description
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Fixes # (issue)
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