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RuntimeError: FlashAttention only supports Ampere GPUs or newer,How to solve

Open zc317414 opened this issue 7 months ago • 1 comments

System Info

docker run -it --gpus all -v E:\infinity:/models -p 8081:8081 michaelf34/infinity:latest v2 --model-id "/models/jinaai/jina-reranker-v2-base-multilingual" --port 8081 INFO: Started server process [1] INFO: Waiting for application startup. INFO 2025-05-21 02:32:46,009 infinity_emb INFO: Creating 1engines: infinity_server.py:84 engines=['jinaai/jina-reranker-v2-base-multilingual'] INFO 2025-05-21 02:32:46,024 infinity_emb INFO: Anonymized telemetry can be disabled via environment telemetry.py:30 variable DO_NOT_TRACK=1. INFO 2025-05-21 02:32:46,054 infinity_emb INFO: select_model.py:64 model=/models/jinaai/jina-reranker-v2-base-multilingual selected, using engine=torch and device=None /app/.venv/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py:985: FutureWarning: torch.cuda.amp.custom_fwd(args...) is deprecated. Please use torch.amp.custom_fwd(args..., device_type='cuda') instead. def forward( /app/.venv/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py:1044: FutureWarning: torch.cuda.amp.custom_bwd(args...) is deprecated. Please use torch.amp.custom_bwd(args..., device_type='cuda') instead. def backward(ctx, dout, *args): ERROR: Traceback (most recent call last): File "/app/.venv/lib/python3.10/site-packages/starlette/routing.py", line 693, in lifespan async with self.lifespan_context(app) as maybe_state: File "/usr/lib/python3.10/contextlib.py", line 199, in aenter return await anext(self.gen) File "/app/infinity_emb/infinity_server.py", line 88, in lifespan app.engine_array = AsyncEngineArray.from_args(engine_args_list) # type: ignore File "/app/infinity_emb/engine.py", line 306, in from_args return cls(engines=tuple(engines)) File "/app/infinity_emb/engine.py", line 71, in from_args engine = cls(**engine_args.to_dict(), _show_deprecation_warning=False) File "/app/infinity_emb/engine.py", line 56, in init self._model_replicas, self._min_inference_t, self._max_inference_t = select_model( File "/app/infinity_emb/inference/select_model.py", line 88, in select_model min(loaded_engine.warmup(batch_size=1, n_tokens=1)[1] for _ in range(10)), File "/app/infinity_emb/inference/select_model.py", line 88, in min(loaded_engine.warmup(batch_size=1, n_tokens=1)[1] for _ in range(10)), File "/app/infinity_emb/transformer/abstract.py", line 220, in warmup return run_warmup(self, inp) File "/app/infinity_emb/transformer/abstract.py", line 233, in run_warmup embed = model.encode_core(feat) File "/app/infinity_emb/transformer/crossencoder/torch.py", line 106, in encode_core out_features = self.model(**features, return_dict=True)["logits"] File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/modeling_xlm_roberta.py", line 854, in forward outputs = self.roberta( File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/modeling_xlm_roberta.py", line 664, in forward sequence_output = self.encoder( File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/modeling_xlm_roberta.py", line 231, in forward hidden_states = layer(hidden_states, mixer_kwargs=mixer_kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/block.py", line 260, in forward mixer_out = self.mixer( File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/mha.py", line 605, in forward context = self.inner_attn(qkv, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl return forward_call(*args, **kwargs) File "/app/.cache/huggingface/modules/transformers_modules/jina-reranker-v2-base-multilingual/mha.py", line 84, in forward return flash_attn_varlen_qkvpacked_func( File "/app/.venv/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 1267, in flash_attn_varlen_qkvpacked_func return FlashAttnVarlenQKVPackedFunc.apply( File "/app/.venv/lib/python3.10/site-packages/torch/autograd/function.py", line 575, in apply return super().apply(*args, **kwargs) # type: ignore[misc] File "/app/.venv/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 553, in forward out_padded, softmax_lse, S_dmask, rng_state = _wrapped_flash_attn_varlen_forward( File "/app/.venv/lib/python3.10/site-packages/torch/_ops.py", line 1123, in call return self._op(*args, **(kwargs or {})) File "/app/.venv/lib/python3.10/site-packages/torch/_library/autograd.py", line 113, in autograd_impl result = forward_no_grad(*args, Metadata(keyset, keyword_only_args)) File "/app/.venv/lib/python3.10/site-packages/torch/_library/autograd.py", line 40, in forward_no_grad result = op.redispatch(keyset & _C._after_autograd_keyset, *args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/_ops.py", line 728, in redispatch return self._handle.redispatch_boxed(keyset, *args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/_library/custom_ops.py", line 305, in backend_impl result = self._backend_fns[device_type](*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/_compile.py", line 32, in inner return disable_fn(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 745, in _fn return fn(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/torch/_library/custom_ops.py", line 337, in wrapped_fn return fn(*args, **kwargs) File "/app/.venv/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 170, in _flash_attn_varlen_forward out, softmax_lse, S_dmask, rng_state = flash_attn_gpu.varlen_fwd( RuntimeError: FlashAttention only supports Ampere GPUs or newer.

Information

  • [x] Docker + cli
  • [ ] pip + cli
  • [ ] pip + usage of Python interface

Tasks

  • [ ] An officially supported CLI command
  • [ ] My own modifications

Reproduction

Image

zc317414 avatar May 21 '25 02:05 zc317414

docker run -it --gpus all -v E:\infinity:/models -p 8081:8081 michaelf34/infinity:latest v2 --no-bettertransformer --model-id "/models/jinaai/jina-reranker-v2-base-multilingual" --port 8081

add --no-bettertransformer , but the above error is still not resolved

zc317414 avatar May 21 '25 03:05 zc317414