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@@ -46,8 +46,11 @@ class ModelSingleton:
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batch_size = kwargs.get("batch_size", 0) # for transformers backend only
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max_concurrency = kwargs.get("max_concurrency", 100) # for http-client backend only
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http_timeout = kwargs.get("http_timeout", 600) # for http-client backend only
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+ server_headers = kwargs.get("server_headers", None) # for http-client backend only
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+ max_retries = kwargs.get("max_retries", 3) # for http-client backend only
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+ retry_backoff_factor = kwargs.get("retry_backoff_factor", 0.5) # for http-client backend only
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# 从kwargs中移除这些参数,避免传递给不相关的初始化函数
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- for param in ["batch_size", "max_concurrency", "http_timeout"]:
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+ for param in ["batch_size", "max_concurrency", "http_timeout", "server_headers", "max_retries", "retry_backoff_factor"]:
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if param in kwargs:
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del kwargs[param]
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if backend not in ["http-client"] and not model_path:
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@@ -175,6 +178,9 @@ class ModelSingleton:
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batch_size=batch_size,
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max_concurrency=max_concurrency,
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http_timeout=http_timeout,
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+ server_headers=server_headers,
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+ max_retries=max_retries,
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+ retry_backoff_factor=retry_backoff_factor,
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)
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elapsed = round(time.time() - start_time, 2)
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logger.info(f"get {backend} predictor cost: {elapsed}s")
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