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[None][chore] Defer exposing context parallel configs #9552

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[None][chore] Defer exposing context parallel configs #9552

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6 changes: 0 additions & 6 deletions tensorrt_llm/bench/benchmark/low_latency.py
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Original file line number Diff line number Diff line change
Expand Up @@ -121,12 +121,6 @@
default=1,
help="pipeline parallelism size",
)
@optgroup.option(
"--cp",
type=int,
default=1,
help="context parallelism size",
)
@optgroup.option(
"--ep",
type=int,
Expand Down
6 changes: 0 additions & 6 deletions tensorrt_llm/bench/benchmark/throughput.py
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Original file line number Diff line number Diff line change
Expand Up @@ -202,12 +202,6 @@
default=1,
help="pipeline parallelism size",
)
@optgroup.option(
"--cp",
type=int,
default=1,
help="context parallelism size",
)
@optgroup.option(
"--ep",
type=int,
Expand Down
20 changes: 1 addition & 19 deletions tensorrt_llm/commands/eval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,6 @@
from ..llmapi import BuildConfig, KvCacheConfig
from ..llmapi.llm_utils import update_llm_args_with_extra_options
from ..logger import logger, severity_map
from ..mapping import CpType


@click.group()
Expand Down Expand Up @@ -75,10 +74,6 @@
type=int,
default=1,
help='Pipeline parallelism size.')
@click.option("--cp_size",
type=int,
default=1,
help='Context parallelism size.')
@click.option("--ep_size",
type=int,
default=None,
Expand Down Expand Up @@ -110,18 +105,14 @@
is_flag=True,
default=False,
help="Flag for disabling KV cache reuse.")
@click.option("--cp_config",
type=dict,
default=None,
help="Context parallelism configuration as JSON.")
@click.pass_context
def main(ctx, model: str, tokenizer: Optional[str], log_level: str,
backend: str, max_beam_width: int, max_batch_size: int,
max_num_tokens: int, max_seq_len: int, tp_size: int, pp_size: int,
ep_size: Optional[int], gpus_per_node: Optional[int],
kv_cache_free_gpu_memory_fraction: float, trust_remote_code: bool,
revision: Optional[str], extra_llm_api_options: Optional[str],
disable_kv_cache_reuse: bool, cp_size: int, cp_config: Optional[dict]):
disable_kv_cache_reuse: bool):
logger.set_level(log_level)
build_config = BuildConfig(max_batch_size=max_batch_size,
max_num_tokens=max_num_tokens,
Expand All @@ -132,20 +123,11 @@ def main(ctx, model: str, tokenizer: Optional[str], log_level: str,
free_gpu_memory_fraction=kv_cache_free_gpu_memory_fraction,
enable_block_reuse=not disable_kv_cache_reuse)

if cp_config is not None and "cp_type" in cp_config:
cp_config = cp_config.copy()
try:
cp_config["cp_type"] = CpType[cp_config["cp_type"].upper()]
except KeyError:
raise ValueError(f"Invalid cp_type: {cp_config['cp_type']}. " \
f"Must be one of: {', '.join([t.name for t in CpType])}")
llm_args = {
"model": model,
"tokenizer": tokenizer,
"tensor_parallel_size": tp_size,
"pipeline_parallel_size": pp_size,
"context_parallel_size": cp_size,
"cp_config": cp_config if cp_config is not None else {},
"moe_expert_parallel_size": ep_size,
"gpus_per_node": gpus_per_node,
"trust_remote_code": trust_remote_code,
Expand Down
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