e03ab82dd2
Signed-off-by: Alex Brooks <albrooks@redhat.com> Signed-off-by: Sy03 <1370724210@qq.com> Signed-off-by: Yueqian Lin <linyueqian@outlook.com> Signed-off-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com> Co-authored-by: Sy03 <1370724210@qq.com> Co-authored-by: Yueqian Lin <linyueqian@outlook.com> Co-authored-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
119 lines
3.7 KiB
Python
119 lines
3.7 KiB
Python
"""Output modality types for vLLM-Omni.
|
|
|
|
This module defines the OutputModality enum and TensorAccumulationStrategy
|
|
for type-safe multimodal output routing and tensor merging.
|
|
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import re
|
|
from enum import Enum, Flag, StrEnum, auto
|
|
|
|
_MODALITY_ALIASES: dict[str, str] = {
|
|
"speech": "audio",
|
|
"images": "image",
|
|
"latents": "latent",
|
|
"wav": "audio",
|
|
"waveform": "audio",
|
|
"pixel_values": "image",
|
|
"pixels": "image",
|
|
}
|
|
|
|
|
|
class OutputModalityNames(StrEnum):
|
|
"""Keys for output modalities.
|
|
|
|
TODO: (Alex) Integrate this with the big-flag enum below + throughout the code
|
|
for better type safety (currently only used for output processor).
|
|
"""
|
|
|
|
TEXT = "text"
|
|
IMAGE = "image"
|
|
AUDIO = "audio"
|
|
LATENT = "latent"
|
|
|
|
|
|
# Specify which output modalities may be drained when handling delta messages.
|
|
# For some types, e.g., latents, we need to be careful to ensure the full context
|
|
# is passed as the stream yields due to assumptions in the I/O processing and model
|
|
# when async chunk isn't enabled.
|
|
NON_DRAINABLE_MODALITIES = {OutputModalityNames.TEXT, OutputModalityNames.LATENT}
|
|
DRAINABLE_MODALITIES = {mod for mod in OutputModalityNames if mod not in NON_DRAINABLE_MODALITIES}
|
|
|
|
|
|
class OutputModality(Flag):
|
|
"""Bit-flag enum for output modalities.
|
|
|
|
Compose freely with ``|`` — no need to enumerate every combination.
|
|
|
|
Single: ``OutputModality.TEXT``, ``OutputModality.IMAGE``, ...
|
|
Compound: ``OutputModality.TEXT | OutputModality.IMAGE`` (text+image)
|
|
|
|
Note: POOLING is intentionally excluded. Pooling/embedding is vLLM's
|
|
native path (pooling_output → PoolingRequestOutput), handled entirely
|
|
by the base OutputProcessor. vLLM-Omni's layer does not participate.
|
|
"""
|
|
|
|
TEXT = auto()
|
|
IMAGE = auto()
|
|
AUDIO = auto()
|
|
LATENT = auto()
|
|
|
|
@classmethod
|
|
def from_string(cls, s: str | None) -> OutputModality:
|
|
"""Parse a free-text modality string into an OutputModality flag.
|
|
|
|
Handles common aliases and compound strings separated by + or ,.
|
|
|
|
Examples::
|
|
|
|
OutputModality.from_string("text+image")
|
|
# → OutputModality.TEXT | OutputModality.IMAGE
|
|
"""
|
|
if not s or not s.strip():
|
|
return cls.TEXT
|
|
|
|
parts = [p.strip().lower() for p in re.split(r"[+,]", s.strip())]
|
|
result = cls(0)
|
|
for p in parts:
|
|
p = _MODALITY_ALIASES.get(p, p)
|
|
try:
|
|
result |= cls[p.upper()]
|
|
except KeyError:
|
|
raise ValueError(f"Unknown modality: {p!r}. Supported: {[m.name.lower() for m in cls]}")
|
|
return result
|
|
|
|
@property
|
|
def has_text(self) -> bool:
|
|
return OutputModality.TEXT in self
|
|
|
|
@property
|
|
def has_multimodal(self) -> bool:
|
|
return bool(self & ~OutputModality.TEXT)
|
|
|
|
|
|
class TensorAccumulationStrategy(Enum):
|
|
"""Strategy for merging incremental multimodal tensors."""
|
|
|
|
CONCAT_DIM0 = "concat_dim0"
|
|
"""Concatenate along dimension 0. Used for image/latent tensors."""
|
|
|
|
CONCAT_LAST = "concat_last"
|
|
"""Concatenate along the last dimension. Used for audio waveforms."""
|
|
|
|
APPEND_LIST = "append_list"
|
|
"""Append to a list (no tensor concatenation)."""
|
|
|
|
REPLACE = "replace"
|
|
"""Replace previous tensor entirely with the latest one."""
|
|
|
|
|
|
def get_accumulation_strategy(modality: OutputModality) -> TensorAccumulationStrategy:
|
|
"""Determine tensor merge strategy from the multimodal flags."""
|
|
if OutputModality.AUDIO in modality:
|
|
return TensorAccumulationStrategy.CONCAT_LAST
|
|
if OutputModality.IMAGE in modality or OutputModality.LATENT in modality:
|
|
return TensorAccumulationStrategy.CONCAT_DIM0
|
|
return TensorAccumulationStrategy.CONCAT_DIM0 # default
|