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5d1018495f
* feat(intel): add diffusers support * try to consume upstream container image * Debug * Manually install deps * Map transformers/hf cache dir to modelpath if not specified * fix(compel): update initialization, pass by all gRPC options * fix: add dependencies, implement transformers for xpu * base it from the oneapi image * Add pillow * set threads if specified when launching the API * Skip conda install if intel * defaults to non-intel * ci: add to pipelines * prepare compel only if enabled * Skip conda install if intel * fix cleanup * Disable compel by default * Install torch 2.1.0 with Intel * Skip conda on some setups * Detect python * Quiet output * Do not override system python with conda * Prefer python3 * Fixups * exllama2: do not install without conda (overrides pytorch version) * exllama/exllama2: do not install if not using cuda * Add missing dataset dependency * Small fixups, symlink to python, add requirements * Add neural_speed to the deps * correctly handle model offloading * fix: device_map == xpu * go back at calling python, fixed at dockerfile level * Exllama2 restricted to only nvidia gpus * Tokenizer to xpu
20 lines
531 B
Bash
Executable File
20 lines
531 B
Bash
Executable File
#!/bin/bash
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##
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## A bash script wrapper that runs the diffusers server with conda
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if [ -d "/opt/intel" ]; then
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# Assumes we are using the Intel oneAPI container image
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# https://github.com/intel/intel-extension-for-pytorch/issues/538
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export XPU=1
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else
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export PATH=$PATH:/opt/conda/bin
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# Activate conda environment
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source activate diffusers
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fi
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# get the directory where the bash script is located
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DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
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python $DIR/backend_diffusers.py $@
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