I’m trying to enable lora adapter dynamically with vLLM on AMD MI300x GPU’s.
Below are the steps that I followed to enable lora dynamically:
**VLLM_ALLOW_RUNTIME_LORA_UPDATING=True python3 -m vllm.entrypoints.openai.api_server --model meta-llama/Llama-3.2-3B-Instruct --served-model-name Llama-3.2-3B-Instruct --enable-lora --max-lora-rank 64**
Below are the logs:
`INFO 04-14 16:15:31 [init.py:239] Automatically detected platform rocm.
WARNING 04-14 16:15:32 [api_server.py:759] LoRA dynamic loading & unloading is enabled in the API server. This should ONLY be used for local development!
INFO 04-14 16:15:32 [api_server.py:981] vLLM API server version 0.8.3.dev19+g3eb08ed9
INFO 04-14 16:15:32 [api_server.py:982] args: Namespace(host=None, port=8000, uvicorn_log_level=‘info’, disable_uvicorn_access_log=False, allow_credentials=False, allowed_origins=[‘‘], allowed_methods=[’’], allowed_headers=[‘’], api_key=None, lora_modules=None, prompt_adapters=None, chat_template=None, chat_template_content_format=‘auto’, response_role=‘assistant’, ssl_keyfile=None, ssl_certfile=None, ssl_ca_certs=None, enable_ssl_refresh=False, ssl_cert_reqs=0, root_path=None, middleware=, return_tokens_as_token_ids=False, disable_frontend_multiprocessing=False, enable_request_id_headers=False, enable_auto_tool_choice=False, tool_call_parser=None, tool_parser_plugin=‘’, model=‘meta-llama/Llama-3.2-3B-Instruct’, task=‘auto’, tokenizer=None, hf_config_path=None, skip_tokenizer_init=False, revision=None, code_revision=None, tokenizer_revision=None, tokenizer_mode=‘auto’, trust_remote_code=False, allowed_local_media_path=None, download_dir=None, load_format=‘auto’, config_format=<ConfigFormat.AUTO: ‘auto’>, dtype=‘auto’, kv_cache_dtype=‘auto’, max_model_len=None, guided_decoding_backend=‘xgrammar’, logits_processor_pattern=None, model_impl=‘auto’, distributed_executor_backend=None, pipeline_parallel_size=1, tensor_parallel_size=1, enable_expert_parallel=False, max_parallel_loading_workers=None, ray_workers_use_nsight=False, block_size=None, enable_prefix_caching=None, disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=None, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_partial_prefills=1, max_long_partial_prefills=1, long_prefill_token_threshold=0, max_num_seqs=None, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, hf_overrides=None, enforce_eager=False, max_seq_len_to_capture=8192, disable_custom_all_reduce=False, tokenizer_pool_size=0, tokenizer_pool_type=‘ray’, tokenizer_pool_extra_config=None, limit_mm_per_prompt=None, mm_processor_kwargs=None, disable_mm_preprocessor_cache=False, enable_lora=True, enable_lora_bias=False, max_loras=1, max_lora_rank=64, lora_extra_vocab_size=256, lora_dtype=‘auto’, long_lora_scaling_factors=None, max_cpu_loras=None, fully_sharded_loras=False, enable_prompt_adapter=False, max_prompt_adapters=1, max_prompt_adapter_token=0, device=‘auto’, num_scheduler_steps=1, use_tqdm_on_load=True, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=None, speculative_config=None, speculative_model=None, speculative_model_quantization=None, num_speculative_tokens=None, speculative_disable_mqa_scorer=False, speculative_draft_tensor_parallel_size=None, speculative_max_model_len=None, speculative_disable_by_batch_size=None, ngram_prompt_lookup_max=None, ngram_prompt_lookup_min=None, spec_decoding_acceptance_method=‘rejection_sampler’, typical_acceptance_sampler_posterior_threshold=None, typical_acceptance_sampler_posterior_alpha=None, disable_logprobs_during_spec_decoding=None, model_loader_extra_config=None, ignore_patterns=, preemption_mode=None, served_model_name=[‘Llama-3.2-3B-Instruct’], qlora_adapter_name_or_path=None, show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=False, scheduling_policy=‘fcfs’, scheduler_cls=‘vllm.core.scheduler.Scheduler’, override_neuron_config=None, override_pooler_config=None, compilation_config=None, kv_transfer_config=None, worker_cls=‘auto’, worker_extension_cls=‘’, generation_config=‘auto’, override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, additional_config=None, enable_reasoning=False, reasoning_parser=None, disable_cascade_attn=False, disable_log_requests=False, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False, enable_server_load_tracking=False)
INFO 04-14 16:15:44 [config.py:585] This model supports multiple tasks: {‘embed’, ‘generate’, ‘classify’, ‘score’, ‘reward’}. Defaulting to ‘generate’.
INFO 04-14 16:15:44 [arg_utils.py:1868] LORA is experimental on VLLM_USE_V1=1. Falling back to V0 Engine.
WARNING 04-14 16:15:44 [arg_utils.py:1744] The model has a long context length (131072). This may causeOOM during the initial memory profiling phase, or result in low performance due to small KV cache size. Consider setting --max-model-len to a smaller value.
INFO 04-14 16:15:44 [config.py:1552] Disabled the custom all-reduce kernel because it is not supported on AMD GPUs.
INFO 04-14 16:15:44 [api_server.py:241] Started engine process with PID 161
INFO 04-14 16:15:47 [init.py:239] Automatically detected platform rocm.
WARNING 04-14 16:15:48 [api_server.py:759] LoRA dynamic loading & unloading is enabled in the API server. This should ONLY be used for local development!
INFO 04-14 16:15:48 [llm_engine.py:241] Initializing a V0 LLM engine (v0.8.3.dev19+g3eb08ed9) with config: model=‘meta-llama/Llama-3.2-3B-Instruct’, speculative_config=None, tokenizer=‘meta-llama/Llama-3.2-3B-Instruct’, skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=131072, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=True, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend=‘xgrammar’, reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=Llama-3.2-3B-Instruct, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=False, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={“splitting_ops”:,“compile_sizes”:,“cudagraph_capture_sizes”:[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],“max_capture_size”:256}, use_cached_outputs=True,
INFO 04-14 16:15:54 [rocm.py:131] None is not supported in AMD GPUs.
INFO 04-14 16:15:54 [rocm.py:132] Using ROCmFlashAttention backend.
INFO 04-14 16:15:54 [parallel_state.py:954] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, TP rank 0
INFO 04-14 16:15:54 [model_runner.py:1110] Starting to load model meta-llama/Llama-3.2-3B-Instruct…
INFO 04-14 16:15:55 [weight_utils.py:265] Using model weights format [‘.safetensors’]
Loading safetensors checkpoint shards: 0% Completed | 0/2 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 50% Completed | 1/2 [00:00<00:00, 1.51it/s]
Loading safetensors checkpoint shards: 100% Completed | 2/2 [00:02<00:00, 1.55s/it]
Loading safetensors checkpoint shards: 100% Completed | 2/2 [00:02<00:00, 1.42s/it]
INFO 04-14 16:15:58 [loader.py:447] Loading weights took 3.02 seconds
INFO 04-14 16:15:58 [punica_selector.py:18] Using PunicaWrapperGPU.
INFO 04-14 16:15:58 [model_runner.py:1146] Model loading took 7.2754 GB and 3.961958 seconds
ERROR 04-14 16:15:59 [engine.py:448] ‘Keyword argument maxnreg was specified but unrecognised’
ERROR 04-14 16:15:59 [engine.py:448] Traceback (most recent call last):
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 436, in run_mp_engine
ERROR 04-14 16:15:59 [engine.py:448] engine = MQLLMEngine.from_vllm_config(
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 128, in from_vllm_config
ERROR 04-14 16:15:59 [engine.py:448] return cls(
ERROR 04-14 16:15:59 [engine.py:448] ^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 82, in init
ERROR 04-14 16:15:59 [engine.py:448] self.engine = LLMEngine(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/llm_engine.py”, line 283, in init
ERROR 04-14 16:15:59 [engine.py:448] self._initialize_kv_caches()
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/llm_engine.py”, line 432, in _initialize_kv_caches
ERROR 04-14 16:15:59 [engine.py:448] self.model_executor.determine_num_available_blocks())
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/executor/executor_base.py”, line 102, in determine_num_available_blocks
ERROR 04-14 16:15:59 [engine.py:448] results = self.collective_rpc(“determine_num_available_blocks”)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/executor/uniproc_executor.py”, line 56, in collective_rpc
ERROR 04-14 16:15:59 [engine.py:448] answer = run_method(self.driver_worker, method, args, kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/utils.py”, line 2255, in run_method
ERROR 04-14 16:15:59 [engine.py:448] return func(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
ERROR 04-14 16:15:59 [engine.py:448] return func(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/worker.py”, line 229, in determine_num_available_blocks
ERROR 04-14 16:15:59 [engine.py:448] self.model_runner.profile_run()
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
ERROR 04-14 16:15:59 [engine.py:448] return func(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1243, in profile_run
ERROR 04-14 16:15:59 [engine.py:448] self._dummy_run(max_num_batched_tokens, max_num_seqs)
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1354, in _dummy_run
ERROR 04-14 16:15:59 [engine.py:448] self.execute_model(model_input, kv_caches, intermediate_tensors)
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
ERROR 04-14 16:15:59 [engine.py:448] return func(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1742, in execute_model
ERROR 04-14 16:15:59 [engine.py:448] hidden_or_intermediate_states = model_executable(
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1751, in _wrapped_call_impl
ERROR 04-14 16:15:59 [engine.py:448] return self._call_impl(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1762, in _call_impl
ERROR 04-14 16:15:59 [engine.py:448] return forward_call(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 529, in forward
ERROR 04-14 16:15:59 [engine.py:448] model_output = self.model(input_ids, positions, intermediate_tensors,
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/compilation/decorators.py”, line 172, in call
ERROR 04-14 16:15:59 [engine.py:448] return self.forward(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 350, in forward
ERROR 04-14 16:15:59 [engine.py:448] hidden_states = self.get_input_embeddings(input_ids)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 337, in get_input_embeddings
ERROR 04-14 16:15:59 [engine.py:448] return self.embed_tokens(input_ids)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1751, in _wrapped_call_impl
ERROR 04-14 16:15:59 [engine.py:448] return self._call_impl(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1762, in _call_impl
ERROR 04-14 16:15:59 [engine.py:448] return forward_call(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/layers.py”, line 264, in forward
ERROR 04-14 16:15:59 [engine.py:448] self.punica_wrapper.add_lora_embedding(full_output,
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/punica_wrapper/punica_gpu.py”, line 176, in add_lora_embedding
ERROR 04-14 16:15:59 [engine.py:448] lora_expand(
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_ops.py”, line 1158, in call
ERROR 04-14 16:15:59 [engine.py:448] return self._op(*args, **(kwargs or {}))
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
ERROR 04-14 16:15:59 [engine.py:448] return func(*args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/ops/triton_ops/lora_expand.py”, line 219, in _lora_expand
ERROR 04-14 16:15:59 [engine.py:448] _lora_expand_kernel[grid](
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/triton/runtime/jit.py”, line 368, in
ERROR 04-14 16:15:59 [engine.py:448] return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
ERROR 04-14 16:15:59 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-14 16:15:59 [engine.py:448] File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/triton/runtime/jit.py”, line 596, in run
ERROR 04-14 16:15:59 [engine.py:448] raise KeyError(“Keyword argument %s was specified but unrecognised” % k)
ERROR 04-14 16:15:59 [engine.py:448] KeyError: ‘Keyword argument maxnreg was specified but unrecognised’
Process SpawnProcess-1:
Traceback (most recent call last):
File “/opt/conda/envs/py_3.12/lib/python3.12/multiprocessing/process.py”, line 314, in _bootstrap
self.run()
File “/opt/conda/envs/py_3.12/lib/python3.12/multiprocessing/process.py”, line 108, in run
self._target(*self._args, **self._kwargs)
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 450, in run_mp_engine
raise e
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 436, in run_mp_engine
engine = MQLLMEngine.from_vllm_config(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 128, in from_vllm_config
return cls(
^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/multiprocessing/engine.py”, line 82, in init
self.engine = LLMEngine(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/llm_engine.py”, line 283, in init
self._initialize_kv_caches()
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/engine/llm_engine.py”, line 432, in _initialize_kv_caches
self.model_executor.determine_num_available_blocks())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/executor/executor_base.py”, line 102, in determine_num_available_blocks
results = self.collective_rpc(“determine_num_available_blocks”)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/executor/uniproc_executor.py”, line 56, in collective_rpc
answer = run_method(self.driver_worker, method, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/utils.py”, line 2255, in run_method
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/worker.py”, line 229, in determine_num_available_blocks
self.model_runner.profile_run()
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1243, in profile_run
self._dummy_run(max_num_batched_tokens, max_num_seqs)
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1354, in _dummy_run
self.execute_model(model_input, kv_caches, intermediate_tensors)
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/worker/model_runner.py”, line 1742, in execute_model
hidden_or_intermediate_states = model_executable(
^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 529, in forward
model_output = self.model(input_ids, positions, intermediate_tensors,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/compilation/decorators.py”, line 172, in call
return self.forward(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 350, in forward
hidden_states = self.get_input_embeddings(input_ids)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/model_executor/models/llama.py”, line 337, in get_input_embeddings
return self.embed_tokens(input_ids)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py”, line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/layers.py”, line 264, in forward
self.punica_wrapper.add_lora_embedding(full_output,
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/punica_wrapper/punica_gpu.py”, line 176, in add_lora_embedding
lora_expand(
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_ops.py”, line 1158, in call
return self._op(*args, **(kwargs or {}))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_contextlib.py”, line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/lora/ops/triton_ops/lora_expand.py”, line 219, in _lora_expand
_lora_expand_kernel[grid](
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/triton/runtime/jit.py”, line 368, in
return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/triton/runtime/jit.py”, line 596, in run
raise KeyError(“Keyword argument %s was specified but unrecognised” % k)
KeyError: ‘Keyword argument maxnreg was specified but unrecognised’
[rank0]:[W414 16:15:59.861372715 ProcessGroupNCCL.cpp:1477] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see Distributed communication package - torch.distributed — PyTorch 2.6 documentation (function operator())
Traceback (most recent call last):
File “”, line 198, in _run_module_as_main
File “”, line 88, in _run_code
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py”, line 1066, in
uvloop.run(run_server(args))
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/uvloop/init.py”, line 109, in run
return __asyncio.run(
^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/asyncio/runners.py”, line 195, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/asyncio/runners.py”, line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “uvloop/loop.pyx”, line 1518, in uvloop.loop.Loop.run_until_complete
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/uvloop/init.py”, line 61, in wrapper
return await main
^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py”, line 1016, in run_server
async with build_async_engine_client(args) as engine_client:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/contextlib.py”, line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py”, line 141, in build_async_engine_client
async with build_async_engine_client_from_engine_args(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/contextlib.py”, line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File “/opt/conda/envs/py_3.12/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py”, line 264, in build_async_engine_client_from_engine_args
raise RuntimeError(
`
vLLM version: 0.8.3.dev19+g3eb08ed9.rocm634
Please let me know If I’m missing anything here?