Improved Tensor Dimension Handling in predict_masks Method for fine tuning

[sushmanthreddy]

close #581

1. Introduction of Conditional Check:

   • In the enhanced predict_masks method, a conditional check is introduced to ascertain whether the image_embeddings tensor's batch size aligns with that of tokens.
   • The check (if image_embeddings.shape[0] != tokens.shape[0]:) is crucial as it guides the subsequent operation: torch.repeat_interleave.

2. Usage of torch.repeat_interleave:

   • The function torch.repeat_interleave is utilized to expand the image_embeddings tensor along the batch dimension to match the batch size of tokens, ensuring consistency in tensor dimensions as the method progresses.
   • In the original implementation, torch.repeat_interleave is applied directly, potentially leading to misalignments in tensor dimensions if the batch sizes are already aligned.

3. Ensuring Consistency:

   • The conditional check ensures that torch.repeat_interleave is applied only when necessary, preventing potential dimension misalignment and ensuring consistent tensor handling within the predict_masks method.

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[sushmanthreddy]

@HannaMao can u pls review this pull request?