[CI/Build] Remove unnecessary flags from test registry (#27353)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-10-23 22:42:40 +08:00
committed by GitHub
parent 237cf6d32a
commit fe2016de2d
13 changed files with 89 additions and 123 deletions

View File

@@ -36,9 +36,7 @@ import torch
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange
from packaging.version import Version
from transformers import BatchFeature
from transformers import __version__ as TRANSFORMERS_VERSION
from transformers.models.glm4v.configuration_glm4v import Glm4vVisionConfig
from transformers.models.glm4v.image_processing_glm4v import (
Glm4vImageProcessor,
@@ -1270,14 +1268,7 @@ class Glm4vMultiModalProcessor(BaseMultiModalProcessor[Glm4vProcessingInfo]):
video_mm_data = dict()
video_mm_data["videos"] = [[video_array]]
# backward compatibility for Transformers 4.55
unuse_metadata = ["do_sample_frames"]
if (
not hasattr(VideoMetadata, "frames_indices")
and "frames_indices" in metadata
):
unuse_metadata.append("frames_indices")
video_mm_data["video_metadata"] = [
[
VideoMetadata(
@@ -1296,24 +1287,11 @@ class Glm4vMultiModalProcessor(BaseMultiModalProcessor[Glm4vProcessingInfo]):
mm_kwargs=video_mm_kwargs,
tok_kwargs=tok_kwargs,
)
if not video_mm_kwargs["do_sample_frames"] and Version(
TRANSFORMERS_VERSION
) < Version("4.56.0"):
# Transformers v4.55 has incorrect timestamps issue for
# skip sampling. We construct the placeholder manually to
# get placeholders with correct timestamps.
placeholder = self.info._construct_video_placeholder(
video_array,
metadata,
video_outputs["video_grid_thw"].squeeze(0),
)
video_placeholder = processor.tokenizer.decode(placeholder)
else:
input_ids = video_outputs.pop("input_ids")
input_ids[input_ids == processor.image_token_id] = (
processor.video_token_id
)
video_placeholder = processor.tokenizer.batch_decode(input_ids)[0]
input_ids = video_outputs.pop("input_ids")
input_ids[input_ids == processor.image_token_id] = (
processor.video_token_id
)
video_placeholder = processor.tokenizer.batch_decode(input_ids)[0]
prompt = prompt.replace(
"<|begin_of_video|><|video|><|end_of_video|>",
video_placeholder,