Comments (1)
The forward pass and the generation function of the model implement the normalization step for the query features, so get_visual_embs()
doesn't implement this.
For the CC3M embedding matrix it's normalized when it's loaded from disk rather than during the extract_img_embs.py
script.
Hope that helps!
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Related Issues (20)
- Clarification on precomputing the visual embeddings HOT 1
- How to get cc3m_embeddings HOT 1
- About the running log HOT 4
- How could this affect the performance? HOT 10
- About error when running Precomputing Text Embeddings and Train HOT 2
- shape mismatch in the example notebook HOT 2
- [solved]
- why don't you use universal representation in one task?
- GILL Image Retrieval Code on VIST HOT 1
- Inference shape is not 8 HOT 1
- Visdial相关问题
- Error size mismatch when load decision model HOT 2
- RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
- param.grad is None !
- shape mismatch in the example "Multimodal Dialogue" HOT 1
- FID Evaluation on CC3M and VIST
- i try to dowmload cc3m using tools recommand by readme.md, but the number of picture can be download only 10% . is it normal?
- about [img] token and train data
- environment conflict
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