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Resolve list not recognizable issue (#4957)
Summary: Pull Request resolved: #4957 X-link: facebookresearch/FBGEMM#1978 Resolve the failure: ``` │ /data/users/jianyuhuang/fbsource/genai/msl/../llama4x/llama4x/ops/attention/ │ │ cutlass.py:7 in <module> │ │ │ │ 4 import torch │ │ 5 │ │ 6 try: │ │ ❱ 7 │ from fbgemm_gpu.experimental.gen_ai.attention.cutlass_blackwell_fm │ │ 8 │ │ cutlass_blackwell_fmha_interface as fmha, │ │ 9 │ ) │ │ 10 │ │ │ │ ╭───────────────────────────────── locals ─────────────────────────────────╮ │ │ │ Any = typing.Any │ │ │ │ dataclass = <function dataclass at 0xfffeb659c040> │ │ │ │ Iterable = typing.Iterable │ │ │ │ torch = <module 'torch' from │ │ │ │ '/home/jianyuhuang/.fbpkg_conda_envs/xlformers_msl_rl_conda… │ │ │ │ Tuple = typing.Tuple │ │ │ ╰──────────────────────────────────────────────────────────────────────────╯ │ │ │ │ /home/jianyuhuang/.fbpkg_conda_envs/xlformers_msl_rl_conda_feedstock-df42b69 │ │ /lib/python3.10/site-packages/fbgemm_gpu/experimental/gen_ai/attention/cutla │ │ ss_blackwell_fmha/__init__.py:35 in <module> │ │ │ │ /home/jianyuhuang/.fbpkg_conda_envs/xlformers_msl_rl_conda_feedstock-df42b69 │ │ /lib/python3.10/site-packages/fbgemm_gpu/experimental/gen_ai/attention/cutla │ │ ss_blackwell_fmha/cutlass_blackwell_fmha_custom_op.py:15 in <module> │ ╰──────────────────────────────────────────────────────────────────────────────╯ TypeError: unhashable type: 'list' ``` Reviewed By: jiawenliu64 Differential Revision: D83633629 fbshipit-source-id: f76aa52093814dc4e747a748babe606ce526919e
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fbgemm_gpu/experimental/gen_ai/gen_ai/attention/cutlass_blackwell_fmha/cutlass_blackwell_fmha_custom_op.py

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torch.library.define(
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"blackwell_fmha::fmha_fwd",
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"(Tensor q, Tensor k, Tensor v, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seq_len_q, int? max_seq_len_k, float? softmax_scale, bool? causal, Tensor? seqlen_kv) -> (Tensor, Tensor)",
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tags=[torch.Tag.pt2_compliant_tag],
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tags=torch.Tag.pt2_compliant_tag,
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)
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torch.library.define(
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"blackwell_fmha::fmha_bwd",
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"(Tensor dout, Tensor q, Tensor k, Tensor v, Tensor out, Tensor softmax_lse, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seq_len_q, int? max_seq_len_k, bool? causal) -> (Tensor, Tensor, Tensor)",
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tags=[torch.Tag.pt2_compliant_tag],
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tags=torch.Tag.pt2_compliant_tag,
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)
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