vlm: support video as an input modality (#5888)

This commit is contained in:
Mick
2025-07-10 14:48:35 +08:00
committed by GitHub
parent 4ed57807c2
commit b5e3d6031c
42 changed files with 887 additions and 524 deletions

View File

@@ -65,6 +65,8 @@ class GenerateReqInput:
] = None
# The audio input. Like image data, it can be a file name, a url, or base64 encoded string.
audio_data: Optional[Union[List[AudioDataItem], AudioDataItem]] = None
# The video input. Like image data, it can be a file name, a url, or base64 encoded string.
video_data: Optional[Union[List[List[str]], List[str], str]] = None
# The sampling_params. See descriptions below.
sampling_params: Optional[Union[List[Dict], Dict]] = None
# The request id.
@@ -110,7 +112,11 @@ class GenerateReqInput:
data_parallel_rank: Optional[int] = None
def contains_mm_input(self) -> bool:
return has_valid_data(self.image_data) or has_valid_data(self.audio_data)
return (
has_valid_data(self.image_data)
or has_valid_data(self.video_data)
or has_valid_data(self.audio_data)
)
def normalize_batch_and_arguments(self):
"""
@@ -232,6 +238,7 @@ class GenerateReqInput:
self._normalize_rid(num)
self._normalize_lora_paths(num)
self._normalize_image_data(num)
self._normalize_video_data(num)
self._normalize_audio_data(num)
self._normalize_sampling_params(num)
self._normalize_logprob_params(num)
@@ -300,6 +307,15 @@ class GenerateReqInput:
self.image_data = wrapped_images * self.parallel_sample_num
self.modalities = ["image"] * num
def _normalize_video_data(self, num):
"""Normalize video data for batch processing."""
if self.video_data is None:
self.video_data = [None] * num
elif not isinstance(self.video_data, list):
self.video_data = [self.video_data] * num
elif isinstance(self.video_data, list):
self.video_data = self.video_data * self.parallel_sample_num
def _normalize_audio_data(self, num):
"""Normalize audio data for batch processing."""
if self.audio_data is None:
@@ -408,6 +424,7 @@ class GenerateReqInput:
self.input_embeds[i] if self.input_embeds is not None else None
),
image_data=self.image_data[i],
video_data=self.video_data[i],
audio_data=self.audio_data[i],
sampling_params=self.sampling_params[i],
rid=self.rid[i],
@@ -507,6 +524,8 @@ class EmbeddingReqInput:
image_data: Optional[
Union[List[List[Union[Image, str]]], List[Union[Image, str]], Union[Image, str]]
] = None
# The video input. Like image data, it can be a file name, a url, or base64 encoded string.
video_data: Optional[Union[List[str], str]] = None
# The audio input. Like image data, it can be a file name, a url, or base64 encoded string.
audio_data: Optional[Union[List[str], str]] = None
# The token ids for text; one can either specify text or input_ids.
@@ -578,7 +597,11 @@ class EmbeddingReqInput:
return self.rid
def contains_mm_input(self) -> bool:
return has_valid_data(self.image_data) or has_valid_data(self.audio_data)
return (
has_valid_data(self.image_data)
or has_valid_data(self.video_data)
or has_valid_data(self.audio_data)
)
def __getitem__(self, i):
if self.is_cross_encoder_request: