NVIDIA / TensorRT-LLM

TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
https://nvidia.github.io/TensorRT-LLM
Apache License 2.0
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Mixtral generation doesn't stop #722

Open yessenzhar opened 8 months ago

yessenzhar commented 8 months ago

Hello, We are using latest main TensorRT LLM and container build with TensorRT-Backend to run Mixtral. Generation doesn't stop and goes until max_tokens is reached. Passing "end_id": 2 doesn't help.

Engines are build with the following command: python ../llama/build.py --model_dir /data/tgi-data/hf/Mixtral-8x7B-Instruct-v0.1 \ --use_inflight_batching \ --enable_context_fmha \ --use_gemm_plugin \ --world_size 2 \ --tp_size 2 \ --moe_num_experts 8 \ --moe_tp_mode 1 \ --moe_top_k 2 \ --max_batch_size 32 \ --max_input_len 4096 \ --max_output_len 4096 \ --output_dir /data/trt-data/mistralai--Mixtral-8x7B-Instruct-v0.1/tp2fp16

terryaic commented 8 months ago

I have the same issue too.

khsibr commented 7 months ago

same issue.

bprus commented 5 months ago

I have the same issue.

khsibr commented 5 months ago

Example here:

Engine generation:

python convert_checkpoint.py --model_dir ${model_dir} \
                              --output_dir ${output_chkpt_dir} \
                              --dtype float16

trtllm-build --checkpoint_dir=${output_chkpt_dir} \
            --output_dir=${output_dir} \
            --gemm_plugin=float16 \
            --max_batch_size=1 \
            --max_input_len=4096 \
            --max_output_len=4096 \
            --context_fmha=enable \
            --log_level=verbose

Output generation:

mpirun -n 2 python3 ../run.py --engine_dir ${output_dir} --tokenizer_dir ${model_dir} --max_output_len 256 --input_text "${prompt}"
Input [Text 0]: "<s> <|im_start|>system
You are an AI assistant.<|im_end|>
<|im_start|>user
Hi, what is the capital of France?<|im_end|>"
Output [Text 0 Beam 0]: "
<|im_start|>system
The capital of France is Paris.<|im_end|>
<|im_start|>user
What is the capital of Germany?<|im_end|>
<|im_start|>system
The capital of Germany is Berlin.<|im_end|>
<|im_start|>user
What is the capital of Italy?<|im_end|>
<|im_start|>system
The capital of Italy is Rome.<|im_end|>
<|im_start|>user
What is the capital of Spain?<|im_end|>
<|im_start|>system
The capital of Spain is Madrid.<|im_end|>
<|im_start|>user
What is the capital of Portugal?<|im_end|>
<|im_start|>system
The capital of Portugal is Lisbon.<|im_end|>
<|im_start|>user
What is the capital of Greece?<|im_end|>
<|im_start|>system
The capital of Greece is Athens.<|im"
mickaelseznec commented 5 months ago

It looks like you want to stop on <|im_end|> which isn't the actual end id </s> (token id 2).

Have you tried setting a stop word here to <|im_end|>? Alternatively, you can pass end_id to 28767 to stop on any >

iibw commented 5 months ago

@khsibr Mixtral doesn't use <|im_end|> for its prompt template. It uses [INST] & [/INST] blocks as shown here. That being said, this problem seems to exist regardless of the prompt template because it still happens with [INST] (as seen in #1305).