Failed test case test_model_generate_images for janus model #44792
Description
System Info
transformersversion: 5.3.0.dev0- Platform: Linux-5.4.292-1.el8.elrepo.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 1.7.1
- Safetensors version: 0.5.3
- Accelerate version: 1.12.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.10.0+cu128 (CUDA)
- Using distributed or parallel set-up in script?:
- Using GPU in script?:
- GPU type: NVIDIA A100 80GB PCIe
Who can help?
multimodal models: @zucchini-nlp
Information
- The official example scripts
- My own modified scripts
Tasks
- An officially supported task in the
examplesfolder (such as GLUE/SQuAD, ...) - My own task or dataset (give details below)
Reproduction
git clone https://github.com/huggingface/transformers.git
cd transformers
pip install -e .
export RUN_SLOW=1
pytest -rA tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_generate_images
Expected behavior
test case pass. Although I added patch
--- a/src/transformers/models/janus/modeling_janus.py
+++ b/src/transformers/models/janus/modeling_janus.py
@@ -1285,7 +1285,7 @@ class JanusForConditionalGeneration(JanusPreTrainedModel, GenerationMixin):
input_ids, model_kwargs = self._expand_inputs_for_generation(
input_ids=input_ids,
attention_mask=attention_mask,
- expand_size=generation_config.num_return_sequences,
+ expand_size=generation_config.num_return_sequences or 1,
**model_kwargs,
)
@@ -1315,7 +1315,7 @@ class JanusForConditionalGeneration(JanusPreTrainedModel, GenerationMixin):
# batch_size should account for both conditional/unconditional input; hence multiplied by 2.
batch_size=batch_size * 2,
# we should have at least a cache len of seq_len + num_image_tokens.
- max_cache_len=max(generation_config.max_length, num_image_tokens + seq_len),
+ max_cache_len=max(generation_config.max_length or 0, num_image_tokens + seq_len),
model_kwargs=model_kwargs,
)
it still gets failed.