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Hi experts,
I'm running a 1.3B model on windows with 16GB V100 with below envs, but hit an issue which I couldn't find any clue. Could you please help check it.
TensorRT-LLM version: tag v0.10.0
Installation references: https://github.com/NVIDIA/TensorRT-LLM/blob/v0.10.0/docs/source/installation/windows.md
GPU info:
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 551.61 Driver Version: 551.61 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 Tesla V100-SXM2-16GB TCC | 00000000:00:07.0 Off | 0 |
| N/A 31C P0 38W / 300W | 9MiB / 16384MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
The code is from examples without any change:
cd examples/apps
python chat.py /model_dir /tokenizer_diroutputs:
C:\Program Files\Python310\lib\site-packages\transformers\utils\generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.
_torch_pytree._register_pytree_node(
[TensorRT-LLM] TensorRT-LLM version: 0.10.0
[TensorRT-LLM][INFO] Engine version 0.10.0 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][WARNING] [json.exception.out_of_range.403] key 'cross_attention' not found
[TensorRT-LLM][WARNING] Optional value for parameter cross_attention will not be set.
[TensorRT-LLM][WARNING] Parameter layer_types cannot be read from json:
[TensorRT-LLM][WARNING] [json.exception.out_of_range.403] key 'layer_types' not found
[TensorRT-LLM][WARNING] [json.exception.type_error.302] type must be string, but is null
[TensorRT-LLM][WARNING] Optional value for parameter quant_algo will not be set.
[TensorRT-LLM][WARNING] [json.exception.type_error.302] type must be string, but is null
[TensorRT-LLM][WARNING] Optional value for parameter kv_cache_quant_algo will not be set.
[TensorRT-LLM][WARNING] [json.exception.out_of_range.403] key 'num_medusa_heads' not found
[TensorRT-LLM][WARNING] Optional value for parameter num_medusa_heads will not be set.
[TensorRT-LLM][WARNING] [json.exception.out_of_range.403] key 'max_draft_len' not found
[TensorRT-LLM][WARNING] Optional value for parameter max_draft_len will not be set.
[TensorRT-LLM][INFO] Rank 0 is using GPU 0
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 4
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 4
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 1280
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
Traceback (most recent call last):
File "D:\ljay\trtllm\TensorRT-LLM\examples\apps\chat.py", line 60, in <module>
main(args.model_dir, args.tokenizer)
File "D:\ljay\trtllm\TensorRT-LLM\examples\apps\chat.py", line 49, in main
with GenerationExecutorWorker(model_dir, tokenizer, 1) as executor:
File "C:\Program Files\Python310\lib\site-packages\tensorrt_llm\executor.py", line 514, in __init__
self.engine = tllm.GptManager(engine_dir, executor_type, max_beam_width,
RuntimeError: [TensorRT-LLM][ERROR] CUDA runtime error in cudaDeviceGetDefaultMemPool(&memPool, device): operation not supported (C:\home\jenkins\agent\workspace\L0_MergeReque---cc29e445\llm\cpp\tensorrt_llm\runtime\bufferManager.cpp:211)
Activity
hijkzzz commentedon Jun 23, 2024
Could you try adding the CUDA / TensorRT-LLM related libs path to Windows System$PATH$ environment variables?
Another easier method is to use WSL2.
ljayx commentedon Jun 26, 2024
I added them to PATH, but the issue remains.

By the way, due to some reasons, I can't use WSL2.
hijkzzz commentedon Jun 28, 2024
Similar issue: triton-inference-server/tensorrtllm_backend#328
ljayx commentedon Jul 17, 2024
@hijkzzz It looks like the solution is for vGPUs, what should I do with a bare metal like mine?
nv-guomingz commentedon Nov 14, 2024
Hi @ljayx do u still have further issue or question now? If not, we'll close it soon.