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https://git.datalinker.icu/vllm-project/vllm.git
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[misc] clean up and unify logging (#10999)
Signed-off-by: youkaichao <youkaichao@gmail.com>
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youkaichao
GitHub
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43b05fa314
commit
46004e83a2
@ -2579,45 +2579,40 @@ class VllmConfig:
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self.instance_id = random_uuid()[:5]
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def __str__(self):
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return ("model=%r, speculative_config=%r, tokenizer=%r, "
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"skip_tokenizer_init=%s, tokenizer_mode=%s, revision=%s, "
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"override_neuron_config=%s, tokenizer_revision=%s, "
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"trust_remote_code=%s, dtype=%s, max_seq_len=%d, "
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"download_dir=%r, load_format=%s, tensor_parallel_size=%d, "
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"pipeline_parallel_size=%d, "
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"disable_custom_all_reduce=%s, quantization=%s, "
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"enforce_eager=%s, kv_cache_dtype=%s, "
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"quantization_param_path=%s, device_config=%s, "
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"decoding_config=%r, observability_config=%r, "
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"seed=%d, served_model_name=%s, "
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"num_scheduler_steps=%d, enable_prefix_caching=%s, "
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"use_async_output_proc=%s, mm_processor_kwargs=%s") % \
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(self.model_config.model, self.speculative_config,
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self.model_config.tokenizer,
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self.model_config.skip_tokenizer_init,
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self.model_config.tokenizer_mode,
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self.model_config.revision,
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self.model_config.override_neuron_config,
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self.model_config.tokenizer_revision,
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self.model_config.trust_remote_code,
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self.model_config.dtype,
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self.model_config.max_model_len,
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self.load_config.download_dir,
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self.load_config.load_format,
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self.parallel_config.tensor_parallel_size,
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self.parallel_config.pipeline_parallel_size,
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self.parallel_config.disable_custom_all_reduce,
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self.model_config.quantization,
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self.model_config.enforce_eager,
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self.cache_config.cache_dtype,
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self.model_config.quantization_param_path,
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self.device_config.device, self.decoding_config,
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self.observability_config, self.model_config.seed,
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self.model_config.served_model_name,
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self.scheduler_config.num_scheduler_steps,
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self.cache_config.enable_prefix_caching,
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self.model_config.use_async_output_proc,
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self.model_config.mm_processor_kwargs)
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return (
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f"model={self.model_config.model!r},"
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f" speculative_config={self.speculative_config!r},"
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f" tokenizer={self.model_config.tokenizer!r}, "
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f"skip_tokenizer_init={self.model_config.skip_tokenizer_init},"
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f" tokenizer_mode={self.model_config.tokenizer_mode}, "
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f"revision={self.model_config.revision}, "
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f"override_neuron_config={self.model_config.override_neuron_config},"
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f" tokenizer_revision={self.model_config.tokenizer_revision}, "
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f"trust_remote_code={self.model_config.trust_remote_code}, "
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f"dtype={self.model_config.dtype}, "
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f"max_seq_len={self.model_config.max_model_len},"
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f" download_dir={self.load_config.download_dir!r}, "
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f"load_format={self.load_config.load_format}, "
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f"tensor_parallel_size={self.parallel_config.tensor_parallel_size},"
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f" pipeline_parallel_size={self.parallel_config.pipeline_parallel_size}, " # noqa
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f"disable_custom_all_reduce={self.parallel_config.disable_custom_all_reduce}, " # noqa
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f"quantization={self.model_config.quantization}, "
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f"enforce_eager={self.model_config.enforce_eager}, "
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f"kv_cache_dtype={self.cache_config.cache_dtype}, "
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f"quantization_param_path={self.model_config.quantization_param_path},"
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f" device_config={self.device_config.device}, "
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f"decoding_config={self.decoding_config!r}, "
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f"observability_config={self.observability_config!r}, "
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f"seed={self.model_config.seed}, "
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f"served_model_name={self.model_config.served_model_name}, "
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f"num_scheduler_steps={self.scheduler_config.num_scheduler_steps}, "
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f"multi_step_stream_outputs={self.scheduler_config.multi_step_stream_outputs}, " # noqa
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f"enable_prefix_caching={self.cache_config.enable_prefix_caching}, "
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f"chunked_prefill_enabled={self.scheduler_config.chunked_prefill_enabled}, " # noqa
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f"use_async_output_proc={self.model_config.use_async_output_proc}, "
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f"mm_processor_kwargs={self.model_config.mm_processor_kwargs}, "
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f"pooler_config={self.model_config.pooler_config!r},"
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f" compilation_config={self.compilation_config!r}")
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_current_vllm_config: Optional[VllmConfig] = None
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@ -247,60 +247,12 @@ class LLMEngine:
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)
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logger.info(
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"Initializing an LLM engine (v%s) with config: "
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"model=%r, speculative_config=%r, tokenizer=%r, "
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"skip_tokenizer_init=%s, tokenizer_mode=%s, revision=%s, "
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"override_neuron_config=%s, tokenizer_revision=%s, "
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"trust_remote_code=%s, dtype=%s, max_seq_len=%d, "
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"download_dir=%r, load_format=%s, tensor_parallel_size=%d, "
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"pipeline_parallel_size=%d, "
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"disable_custom_all_reduce=%s, quantization=%s, "
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"enforce_eager=%s, kv_cache_dtype=%s, "
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"quantization_param_path=%s, device_config=%s, "
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"decoding_config=%r, observability_config=%r, "
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"seed=%d, served_model_name=%s, "
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"num_scheduler_steps=%d, chunked_prefill_enabled=%s "
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"multi_step_stream_outputs=%s, enable_prefix_caching=%s, "
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"use_async_output_proc=%s, use_cached_outputs=%s, "
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"mm_processor_kwargs=%s, pooler_config=%r,"
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"compilation_config=%r",
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"Initializing an LLM engine (v%s) with config: %r,"
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"use_cached_outputs=%s, ",
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VLLM_VERSION,
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self.model_config.model,
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self.speculative_config,
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self.model_config.tokenizer,
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self.model_config.skip_tokenizer_init,
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self.model_config.tokenizer_mode,
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self.model_config.revision,
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self.model_config.override_neuron_config,
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self.model_config.tokenizer_revision,
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self.model_config.trust_remote_code,
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self.model_config.dtype,
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self.model_config.max_model_len,
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self.load_config.download_dir,
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self.load_config.load_format,
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self.parallel_config.tensor_parallel_size,
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self.parallel_config.pipeline_parallel_size,
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self.parallel_config.disable_custom_all_reduce,
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self.model_config.quantization,
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self.model_config.enforce_eager,
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self.cache_config.cache_dtype,
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self.model_config.quantization_param_path,
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self.device_config.device,
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self.decoding_config,
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self.observability_config,
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self.model_config.seed,
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self.model_config.served_model_name,
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self.scheduler_config.num_scheduler_steps,
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self.scheduler_config.chunked_prefill_enabled,
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self.scheduler_config.multi_step_stream_outputs,
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self.cache_config.enable_prefix_caching,
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self.model_config.use_async_output_proc,
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vllm_config,
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use_cached_outputs,
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self.model_config.mm_processor_kwargs,
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self.model_config.pooler_config,
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vllm_config.compilation_config,
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)
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# TODO(woosuk): Print more configs in debug mode.
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self.log_stats = log_stats
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self.use_cached_outputs = use_cached_outputs
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