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[Feat] ShareGPT input len #4

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98 changes: 75 additions & 23 deletions vllm/benchmarks/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1235,13 +1235,17 @@
num_requests: int,
lora_path: str | None = None,
max_loras: int | None = None,
input_len: int | None = None,
output_len: int | None = None,
enable_multimodal_chat: bool = False,
request_id_prefix: str = "",
no_oversample: bool = False,
**kwargs,
) -> list:
samples: list = []
new_prompt_cnt = 0
new_prompt = ""
new_prompt_len = 0
ind = 0
for entry in self.data:
if len(samples) >= num_requests:
Expand All @@ -1258,30 +1262,70 @@
completion_ids = tokenizer(completion).input_ids
prompt_len = len(prompt_ids)
new_output_len = len(completion_ids) if output_len is None else output_len
if not is_valid_sequence(
prompt_len,
new_output_len,
skip_min_output_len_check=output_len is not None,
):
continue
if image_path := entry.get("image"):
mm_content = process_image(image_path)
elif video_path := entry.get("video"):
mm_content = process_video(video_path)
if input_len:
# Make fixed size len
remaining_len = input_len - new_prompt_len
if prompt_len > input_len:
continue
if remaining_len > prompt_len:
new_prompt = new_prompt + ' ' + prompt
new_prompt_ids = tokenizer(new_prompt).input_ids
new_prompt_len = len(new_prompt_ids)
continue
else:
new_prompt = new_prompt + tokenizer.decode(prompt_ids[:remaining_len])

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vllm/benchmarks/datasets.py:1276:89: E501 Line too long (90 > 88)
new_prompt_ids = tokenizer(new_prompt).input_ids
new_prompt_len = len(new_prompt_ids)
if not is_valid_sequence(
new_prompt_len,
new_output_len,
min_len=input_len,
max_prompt_len=input_len,
max_total_len=input_len+output_len,
skip_min_output_len_check=output_len is not None,
):
continue
if enable_multimodal_chat:
new_prompt = self.apply_multimodal_chat_transformation(new_prompt, None)

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vllm/benchmarks/datasets.py:1289:89: E501 Line too long (96 > 88)
samples.append(
SampleRequest(
prompt=new_prompt,
prompt_len=new_prompt_len,
expected_output_len=new_output_len,
lora_request=lora_request,
multi_modal_data=None,
request_id=request_id_prefix + str(ind),
)
)
new_prompt_cnt = new_prompt_cnt + 1
if int(new_prompt_cnt % (num_requests / 10)) == 0:
print(f"[{new_prompt_cnt}/{num_requests}] new prompts are created")

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vllm/benchmarks/datasets.py:1302:89: E501 Line too long (91 > 88)
new_prompt = ""
new_prompt_len = 0
else:
mm_content = None
if enable_multimodal_chat:
prompt = self.apply_multimodal_chat_transformation(prompt, mm_content)
samples.append(
SampleRequest(
prompt=prompt,
prompt_len=prompt_len,
expected_output_len=new_output_len,
lora_request=lora_request,
multi_modal_data=mm_content,
request_id=request_id_prefix + str(ind),
)
)
if not is_valid_sequence(prompt_len,
new_output_len,
skip_min_output_len_check=output_len
is not None):
continue
if image_path := entry.get("image"):
mm_content = process_image(image_path)
elif video_path := entry.get("video"):
mm_content = process_video(video_path)
else:
mm_content = None
if enable_multimodal_chat:
prompt = self.apply_multimodal_chat_transformation(
prompt, mm_content)
samples.append(
SampleRequest(
prompt=prompt,
prompt_len=prompt_len,
expected_output_len=new_output_len,
lora_request=lora_request,
multi_modal_data=mm_content,
request_id=request_id_prefix + str(ind),
))
ind += 1
self.maybe_oversample_requests(
samples, num_requests, request_id_prefix, no_oversample
Expand Down Expand Up @@ -1409,6 +1453,13 @@
)

sharegpt_group = parser.add_argument_group("sharegpt dataset options")
sharegpt_group.add_argument(
"--sharegpt-input-len",
type=int,
default=None,
help="Input length for each request. Overrides the input length "
"from the ShareGPT dataset.",
)
sharegpt_group.add_argument(
"--sharegpt-output-len",
type=int,
Expand Down Expand Up @@ -1824,6 +1875,7 @@
).sample(
tokenizer=tokenizer,
num_requests=args.num_prompts,
input_len=args.sharegpt_input_len,
output_len=args.sharegpt_output_len,
request_id_prefix=args.request_id_prefix,
no_oversample=args.no_oversample,
Expand Down
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