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[None][chore] Remove two unused parameters in create_py_executor
Signed-off-by: leslie-fang25 <[email protected]>
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tensorrt_llm/_torch/pyexecutor/py_executor_creator.py

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@@ -217,14 +217,9 @@ def create_py_executor(
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tokenizer: Optional[TokenizerBase] = None,
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lora_config: Optional[LoraConfig] = None,
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kv_connector_config: Optional[KvCacheConnectorConfig] = None,
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logits_post_processor_config: Optional[LogitsPostProcessorConfig] = None,
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parallel_config: Optional[ParallelConfig] = None,
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) -> PyExecutor:
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executor_config = llm_args.get_executor_config(checkpoint_dir, tokenizer)
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executor_config.logits_post_processor_config = logits_post_processor_config
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executor_config.parallel_config = parallel_config
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garbage_collection_gen0_threshold = llm_args.garbage_collection_gen0_threshold
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_mangle_executor_config(executor_config)

tensorrt_llm/executor/worker.py

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@@ -122,13 +122,6 @@ def _create_py_executor():
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args["tokenizer"] = tokenizer
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args["lora_config"] = lora_config
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args["kv_connector_config"] = kv_connector_config
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args[
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"logits_post_processor_config"] = tllm.LogitsPostProcessorConfig(
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processor_batched=batched_logits_processor,
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replicate=False)
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comm_ranks, device_ids = _get_comm_ranks_device_id()
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args["parallel_config"] = tllm.ParallelConfig(
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participant_ids=comm_ranks, device_ids=device_ids)
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elif self.llm_args.backend == "_autodeploy":
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from tensorrt_llm._torch.auto_deploy.llm_args import \
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LlmArgs as ADLlmArgs

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