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[Core] Support image processor (#4197)

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This commit is contained in:
Cyrus Leung
2024-06-03 13:56:41 +08:00
committed by GitHub
parent dfbe60dc62
commit 7a64d24aad
29 changed files with 1042 additions and 256 deletions
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108
vllm/engine/arg_utils.py
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@@ -1,6 +1,7 @@
import argparse
import dataclasses
import json
import warnings
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
@@ -80,6 +81,10 @@ class EngineArgs:
image_token_id: Optional[int] = None
image_input_shape: Optional[str] = None
image_feature_size: Optional[int] = None
image_processor: Optional[str] = None
image_processor_revision: Optional[str] = None
disable_image_processor: bool = False
scheduler_delay_factor: float = 0.0
enable_chunked_prefill: bool = False
@@ -98,6 +103,53 @@ class EngineArgs:
if self.tokenizer is None:
self.tokenizer = self.model
@staticmethod
def add_cli_args_for_vlm(
parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
parser.add_argument('--image-input-type',
type=nullable_str,
default=None,
choices=[
t.name.lower()
for t in VisionLanguageConfig.ImageInputType
],
help=('The image input type passed into vLLM.'))
parser.add_argument('--image-token-id',
type=int,
default=None,
help=('Input id for image token.'))
parser.add_argument(
'--image-input-shape',
type=nullable_str,
default=None,
help=('The biggest image input shape (worst for memory footprint) '
'given an input type. Only used for vLLM\'s profile_run.'))
parser.add_argument(
'--image-feature-size',
type=int,
default=None,
help=('The image feature size along the context dimension.'))
parser.add_argument(
'--image-processor',
type=str,
default=EngineArgs.image_processor,
help='Name or path of the huggingface image processor to use. '
'If unspecified, model name or path will be used.')
parser.add_argument(
'--image-processor-revision',
type=str,
default=None,
help='Revision of the huggingface image processor version to use. '
'It can be a branch name, a tag name, or a commit id. '
'If unspecified, will use the default version.')
parser.add_argument(
'--disable-image-processor',
action='store_true',
help='Disables the use of image processor, even if one is defined '
'for the model on huggingface.')
return parser
@staticmethod
def add_cli_args(
parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
@@ -113,7 +165,8 @@ class EngineArgs:
'--tokenizer',
type=nullable_str,
default=EngineArgs.tokenizer,
help='Name or path of the huggingface tokenizer to use.')
help='Name or path of the huggingface tokenizer to use. '
'If unspecified, model name or path will be used.')
parser.add_argument(
'--skip-tokenizer-init',
action='store_true',
@@ -136,9 +189,9 @@ class EngineArgs:
'--tokenizer-revision',
type=nullable_str,
default=None,
help='The specific tokenizer version to use. It can be a branch '
'name, a tag name, or a commit id. If unspecified, will use '
'the default version.')
help='Revision of the huggingface tokenizer to use. '
'It can be a branch name, a tag name, or a commit id. '
'If unspecified, will use the default version.')
parser.add_argument(
'--tokenizer-mode',
type=str,
@@ -445,31 +498,10 @@ class EngineArgs:
default=EngineArgs.device,
choices=["auto", "cuda", "neuron", "cpu"],
help='Device type for vLLM execution.')
# Related to Vision-language models such as llava
parser.add_argument(
'--image-input-type',
type=nullable_str,
default=None,
choices=[
t.name.lower() for t in VisionLanguageConfig.ImageInputType
],
help=('The image input type passed into vLLM. '
'Should be one of "pixel_values" or "image_features".'))
parser.add_argument('--image-token-id',
type=int,
default=None,
help=('Input id for image token.'))
parser.add_argument(
'--image-input-shape',
type=nullable_str,
default=None,
help=('The biggest image input shape (worst for memory footprint) '
'given an input type. Only used for vLLM\'s profile_run.'))
parser.add_argument(
'--image-feature-size',
type=int,
default=None,
help=('The image feature size along the context dimension.'))
parser = EngineArgs.add_cli_args_for_vlm(parser)
parser.add_argument(
'--scheduler-delay-factor',
type=float,
@@ -488,7 +520,6 @@ class EngineArgs:
default=EngineArgs.speculative_model,
help=
'The name of the draft model to be used in speculative decoding.')
parser.add_argument(
'--num-speculative-tokens',
type=int,
@@ -666,12 +697,27 @@ class EngineArgs:
raise ValueError(
'Specify `image_token_id`, `image_input_shape` and '
'`image_feature_size` together with `image_input_type`.')
if self.image_processor is None:
self.image_processor = self.model
if self.disable_image_processor:
if self.image_processor != self.model:
warnings.warn(
"You've specified an image processor "
f"({self.image_processor}) but also disabled "
"it via `--disable-image-processor`.",
stacklevel=2)
self.image_processor = None
vision_language_config = VisionLanguageConfig(
image_input_type=VisionLanguageConfig.
get_image_input_enum_type(self.image_input_type),
image_token_id=self.image_token_id,
image_input_shape=str_to_int_tuple(self.image_input_shape),
image_feature_size=self.image_feature_size,
image_processor=self.image_processor,
image_processor_revision=self.image_processor_revision,
)
else:
vision_language_config = None
@@ -734,3 +780,7 @@ def _engine_args_parser():
def _async_engine_args_parser():
return AsyncEngineArgs.add_cli_args(argparse.ArgumentParser(),
async_args_only=True)
def _vlm_engine_args_parser():
return EngineArgs.add_cli_args_for_vlm(argparse.ArgumentParser())