Reduce RAM high usage during evaluation

[ManuelFay]

Description

The current implementation loads the whole dataset in the RAM during evaluation, which causes unneeded high RAM spikes. This PR reuses the batching strategy already used during inference in a pre-batching step to drastically reduce the RAM usage.

Features

Changed

• Add better RAM handling during evaluation

Fixed

• Fix issue when no pretrained_model_name_or_path is None in load_vision_retriever_from_registry

Test

E2E tested with:

vidore-benchmark evaluate-retriever \
    --model-class siglip \
    --model-name google/siglip-so400m-patch14-384 \
    --dataset-name vidore/shiftproject_test \
    --split test