NVIDIA / NVIDIA/TensorRT-LLM

Can't build whisper engines with past two releases

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#2,508 7 comments 0 reactions 1 assignee View on GitHub

@yuekaizhang is already working on this.

Since Dec 10, 2024.

bug Model customization Testing triaged
Dominant language
Python
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Description

System Info
  • CPU architecture: x86_64
  • CPU/Host memory size: 512GB
  • GPU properties
    • GPU name: 2xNVIDIA H100
  • Libraries
    • TensorRT-LLM branch or tag: v0.16.0dev2024111900 or higher
    • Versions of TensorRT, Modelopt, CUDA, cuBLAS, etc. used: the ones in the requirements
Who can help?

@byshiue

Information
  • The official example scripts
  • My own modified scripts
Tasks
  • An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
  • My own task or dataset (give details below)
Reproduction
trtllm-build  --checkpoint_dir trt/whisper_large-v2_weights_int8/encoder \
              --output_dir trt/whisper_large-v2_int8_2/encoder \
              --kv_cache_type paged \
              --moe_plugin disable \
              --enable_xqa enable \
              --max_batch_size 16 \
              --gemm_plugin disable \
              --bert_attention_plugin float16 \
              --max_input_len 3000 \
              --max_seq_len 3000 \
              --log_level debug \
              --enable_debug_output
Expected behavior

Engine builds successfully and fast

actual behavior

Whisper Large-V2 encoder hangs when building the engine
this is the last thing printed before it hangs: [11/27/2024-23:00:09] [TRT] [V] Disabling unused tactic source: JIT_CONVOLUTIONS
I tried waiting for around an hour but it still didn't complete and nvidia-smi memory usage for the process was constant

Tiny model builds fine but it's much slower than older versions

additional notes

None

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