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Update backend/main.py
Browse files- backend/main.py +3 -10
backend/main.py
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@@ -40,15 +40,6 @@ import socketio
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###############################################
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# Configure logger
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# logging.basicConfig(filename="backend.log",
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# filemode='w',
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# format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
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# datefmt='%H:%M:%S',
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# level=logging.DEBUG)
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# logger = logging.getLogger("socketio_server_pubsub")
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# gunicorn_logger.propagate = True
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gunicorn_error_logger = logging.getLogger("gunicorn.error")
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gunicorn_logger = logging.getLogger("gunicorn")
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uvicorn_access_logger = logging.getLogger("uvicorn.access")
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@@ -143,8 +134,10 @@ static_files = {
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}
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large", cache_dir="/.cache")
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# PM - hardcoding temporarily as my GPU doesnt have enough vram
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model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to("cpu")
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bytes_data = bytearray()
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###############################################
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# Configure logger
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gunicorn_error_logger = logging.getLogger("gunicorn.error")
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gunicorn_logger = logging.getLogger("gunicorn")
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uvicorn_access_logger = logging.getLogger("uvicorn.access")
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}
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large", cache_dir="/.cache")
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# PM - hardcoding temporarily as my GPU doesnt have enough vram
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# model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to("cpu")
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model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to(device)
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bytes_data = bytearray()
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