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[None][chore] Remove two unused parameters in create_py_executor #7458

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Merged
merged 3 commits into from
Sep 3, 2025
Merged

[None][chore] Remove two unused parameters in create_py_executor #7458

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29b705c
[None][chore] Remove two unused parameters in create_py_executor
leslie-fang25 Sep 2, 2025
1e05b8f
code format
leslie-fang25 Sep 2, 2025
fbdc867
add back the comm init
leslie-fang25 Sep 3, 2025
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9 changes: 1 addition & 8 deletions tensorrt_llm/_torch/pyexecutor/py_executor_creator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,7 @@
from tensorrt_llm._utils import get_sm_version
from tensorrt_llm.bindings.executor import (CapacitySchedulerPolicy,
ContextChunkingPolicy,
ExecutorConfig,
LogitsPostProcessorConfig,
ParallelConfig)
ExecutorConfig)
from tensorrt_llm.bindings.internal.batch_manager import ContextChunkingConfig
from tensorrt_llm.llmapi.llm_args import KvCacheConnectorConfig, TorchLlmArgs
from tensorrt_llm.llmapi.tokenizer import TokenizerBase
Expand Down Expand Up @@ -217,14 +215,9 @@ def create_py_executor(
tokenizer: Optional[TokenizerBase] = None,
lora_config: Optional[LoraConfig] = None,
kv_connector_config: Optional[KvCacheConnectorConfig] = None,
logits_post_processor_config: Optional[LogitsPostProcessorConfig] = None,
parallel_config: Optional[ParallelConfig] = None,
) -> PyExecutor:

executor_config = llm_args.get_executor_config(checkpoint_dir, tokenizer)
executor_config.logits_post_processor_config = logits_post_processor_config
executor_config.parallel_config = parallel_config

garbage_collection_gen0_threshold = llm_args.garbage_collection_gen0_threshold

_mangle_executor_config(executor_config)
Expand Down
7 changes: 0 additions & 7 deletions tensorrt_llm/executor/worker.py
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Expand Up @@ -122,13 +122,6 @@ def _create_py_executor():
args["tokenizer"] = tokenizer
args["lora_config"] = lora_config
args["kv_connector_config"] = kv_connector_config
args[
"logits_post_processor_config"] = tllm.LogitsPostProcessorConfig(
processor_batched=batched_logits_processor,
replicate=False)
comm_ranks, device_ids = _get_comm_ranks_device_id()
args["parallel_config"] = tllm.ParallelConfig(
participant_ids=comm_ranks, device_ids=device_ids)
elif self.llm_args.backend == "_autodeploy":
from tensorrt_llm._torch.auto_deploy.llm_args import \
LlmArgs as ADLlmArgs
Expand Down