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fix lint

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2025-07-29 08:39:41 +00:00
parent 1b8d194b67
commit 07cbc51cd1
8 changed files with 165 additions and 157 deletions
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40
runtime/triton_trtllm/scripts/convert_checkpoint.py
View File

@@ -35,8 +35,7 @@ def parse_arguments():
type=str,
default='auto',
choices=['auto', 'float16', 'bfloat16', 'float32'],
help=
"The data type for the model weights and activations if not quantized. "
help="The data type for the model weights and activations if not quantized. "
"If 'auto', the data type is automatically inferred from the source model; "
"however, if the source dtype is float32, it is converted to float16.")
parser.add_argument(
@@ -49,8 +48,7 @@ def parse_arguments():
'--disable_weight_only_quant_plugin',
default=False,
action="store_true",
help=
'By default, using plugin implementation for weight quantization. Enabling disable_weight_only_quant_plugin flag will use ootb implementation instead of plugin.'
help='By default, using plugin implementation for weight quantization. Enabling disable_weight_only_quant_plugin flag will use ootb implementation instead of plugin.'
'You must also use --use_weight_only for that argument to have an impact.'
)
parser.add_argument(
@@ -60,16 +58,14 @@ def parse_arguments():
nargs='?',
default='int8',
choices=['int8', 'int4', 'int4_gptq'],
help=
'Define the precision for the weights when using weight-only quantization.'
help='Define the precision for the weights when using weight-only quantization.'
'You must also use --use_weight_only for that argument to have an impact.'
)
parser.add_argument(
'--calib_dataset',
type=str,
default='ccdv/cnn_dailymail',
help=
"The huggingface dataset name or the local directory of the dataset for calibration."
help="The huggingface dataset name or the local directory of the dataset for calibration."
)
parser.add_argument(
"--smoothquant",
@@ -83,31 +79,27 @@ def parse_arguments():
'--per_channel',
action="store_true",
default=False,
help=
'By default, we use a single static scaling factor for the GEMM\'s result. '
help='By default, we use a single static scaling factor for the GEMM\'s result. '
'per_channel instead uses a different static scaling factor for each channel. '
'The latter is usually more accurate, but a little slower.')
parser.add_argument(
'--per_token',
action="store_true",
default=False,
help=
'By default, we use a single static scaling factor to scale activations in the int8 range. '
help='By default, we use a single static scaling factor to scale activations in the int8 range. '
'per_token chooses at run time, and for each token, a custom scaling factor. '
'The latter is usually more accurate, but a little slower.')
parser.add_argument(
'--int8_kv_cache',
default=False,
action="store_true",
help=
'By default, we use dtype for KV cache. int8_kv_cache chooses int8 quantization for KV'
help='By default, we use dtype for KV cache. int8_kv_cache chooses int8 quantization for KV'
)
parser.add_argument(
'--per_group',
default=False,
action="store_true",
help=
'By default, we use a single static scaling factor to scale weights in the int4 range. '
help='By default, we use a single static scaling factor to scale weights in the int4 range. '
'per_group chooses at run time, and for each group, a custom scaling factor. '
'The flag is built for GPTQ/AWQ quantization.')
@@ -121,16 +113,14 @@ def parse_arguments():
'--use_parallel_embedding',
action="store_true",
default=False,
help=
'By default embedding parallelism is disabled. By setting this flag, embedding parallelism is enabled'
help='By default embedding parallelism is disabled. By setting this flag, embedding parallelism is enabled'
)
parser.add_argument(
'--embedding_sharding_dim',
type=int,
default=0,
choices=[0, 1],
help=
'By default the embedding lookup table is sharded along vocab dimension (embedding_sharding_dim=0). '
help='By default the embedding lookup table is sharded along vocab dimension (embedding_sharding_dim=0). '
'To shard it along hidden dimension, set embedding_sharding_dim=1'
'Note: embedding sharing is only enabled when embedding_sharding_dim = 0'
)
@@ -147,15 +137,13 @@ def parse_arguments():
'--moe_tp_size',
type=int,
default=-1,
help=
'N-way tensor parallelism size for MOE, default is tp_size, which will do tp-only for MoE'
help='N-way tensor parallelism size for MOE, default is tp_size, which will do tp-only for MoE'
)
parser.add_argument(
'--moe_ep_size',
type=int,
default=-1,
help=
'N-way expert parallelism size for MOE, default is 1, which will do tp-only for MoE'
help='N-way expert parallelism size for MOE, default is 1, which will do tp-only for MoE'
)
args = parser.parse_args()
return args
@@ -249,7 +237,7 @@ def convert_and_save_hf(args):
trust_remote_code=True)
quant_config, override_fields = update_quant_config_from_hf(
quant_config, hf_config, override_fields)
except:
except BaseException:
logger.warning("AutoConfig cannot load the huggingface config.")
if args.smoothquant is not None or args.int8_kv_cache:
@@ -339,4 +327,4 @@ def main():
if __name__ == '__main__':
main()
main()

5
runtime/triton_trtllm/scripts/fill_template.py
View File

@@ -1,4 +1,4 @@
#! /usr/bin/env python3
# /usr/bin/env python3
from argparse import ArgumentParser
from string import Template
@@ -59,8 +59,7 @@ if __name__ == "__main__":
parser.add_argument("file_path", help="path of the .pbtxt to modify")
parser.add_argument(
"substitutions",
help=
"substitutions to perform, in the format variable_name_1:value_1,variable_name_2:value_2..."
help="substitutions to perform, in the format variable_name_1:value_1,variable_name_2:value_2..."
)
parser.add_argument("--in_place",
"-i",

3
runtime/triton_trtllm/scripts/test_llm.py
View File

@@ -46,7 +46,6 @@ def parse_arguments(args=None):
parser.add_argument('--top_k', type=int, default=50)
parser.add_argument('--top_p', type=float, default=0.95)
return parser.parse_args(args=args)
@@ -60,7 +59,7 @@ def parse_input(tokenizer,
input_ids = tokenizer.encode(
curr_text)
batch_input_ids.append(input_ids)
batch_input_ids = [
torch.tensor(x, dtype=torch.int32) for x in batch_input_ids
]