1. 26 Apr, 2024 1 commit
    • Wang, Yi's avatar
      add intel xpu support for TGI (#1475) · 45ecf9d0
      Wang, Yi authored
      # What does this PR do?
      
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      ---------
      Signed-off-by: default avatarWang, Yi A <yi.a.wang@intel.com>
      Co-authored-by: default avatarMorgan Funtowicz <funtowiczmo@gmail.com>
      Co-authored-by: default avatarNicolas Patry <patry.nicolas@protonmail.com>
      45ecf9d0
  2. 22 Apr, 2024 1 commit
  3. 04 Apr, 2024 1 commit
    • Nicolas Patry's avatar
      Add cuda graphs sizes and make it default. (#1703) · 99874eae
      Nicolas Patry authored
      # What does this PR do?
      
      ```
      text-generation-launcher --model-id XXX # Uses cuda graphs by default
      text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
      text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
      ```
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      99874eae
  4. 14 Feb, 2024 2 commits
    • Nicolas Patry's avatar
      Small cleanup. (#1560) · 4c2848b2
      Nicolas Patry authored
      Using a single `os.getenv` statement instead of multiple.
      Should make truthful values easier to catch
      
      In the end didn't move towards full CLI because modifying globals in
      Python is error prone (depends on code import order).
      
      Added an error when mamba is launched with TP.
      
      
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      4c2848b2
    • Nicolas Patry's avatar
      Improving mamba runtime by using updates (#1552) · d6b0fb9e
      Nicolas Patry authored
      - Move float16 to bfloat16, which has less imprecisions (load test are
        failing with the update kernels + f16, all working under bf16).
      
        Another note, is that we are not respecting the layer norm in f32
        defined in the configuration (this is OK in my book, but that could
        impact the f16 precision)
      
      - Moved to update kernels. Triton overhead is super high, removed by
        switching to cuda graphs works great (update cuda graph is available
        in TRT-LLM if needed, seems *exactly* like the regular ssm kernel.
      
      - Moved inference_params struct in order to make only 2 tensors, to
        reduce the overhead of copying back and forth to the cuda graphs.
      
      - Left over overhead seems entirely in the tokenization bit. (Still 4
        copies are paid before launching the graph)
      
      
      # What does this PR do?
      
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      d6b0fb9e