fix: limit CPU usage for VAD onnxruntime inference session by setting OMP_NUM_THREADS
Signed-off-by: makaveli10 <vineet.suryan@collabora.com>
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@@ -53,7 +53,13 @@ python3 run_server.py -p 9090 \
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-trt /home/TensorRT-LLM/examples/whisper/whisper_small \
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-m
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```
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#### Controlling OpenMP Threads
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To control the number of threads used by OpenMP, you can set the `OMP_NUM_THREADS` environment variable. This is useful for managing CPU resources and ensuring consistent performance. If not specified, `OMP_NUM_THREADS` is set to `1` by default. You can change this by using the `--omp_num_threads` argument:
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```bash
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python3 run_server.py --port 9090 \
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--backend faster_whisper \
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--omp_num_threads 4
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```
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### Running the Client
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- Initializing the client:
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+9
-1
@@ -1,5 +1,5 @@
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import argparse
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from whisper_live.server import TranscriptionServer
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import os
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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@@ -21,12 +21,20 @@ if __name__ == "__main__":
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parser.add_argument('--trt_multilingual', '-m',
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action="store_true",
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help='Boolean only for TensorRT model. True if multilingual.')
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parser.add_argument('--omp_num_threads', '-omp',
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type=int,
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default=1,
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help="Number of threads to use for OpenMP")
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args = parser.parse_args()
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if args.backend == "tensorrt":
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if args.trt_model_path is None:
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raise ValueError("Please Provide a valid tensorrt model path")
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if "OMP_NUM_THREADS" not in os.environ:
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os.environ["OMP_NUM_THREADS"] = str(args.omp_num_threads)
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from whisper_live.server import TranscriptionServer
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server = TranscriptionServer()
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server.run(
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"0.0.0.0",
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