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Fix group_by_modality_length in sync with LLaVA repo #90

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Fix group_by_modality_length in sync with LLaVA repo #90

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6 changes: 3 additions & 3 deletions tinyllava/train/tinyllava_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,12 +43,12 @@ def split_to_even_chunks(indices, lengths, num_chunks):
def get_modality_length_grouped_indices(lengths, batch_size, world_size, generator=None):
# We need to use torch for the random part as a distributed sampler will set the random seed for torch.
assert all(l != 0 for l in lengths), "Should not have zero length."
if all(l > 0 for l in lengths) or all(l < 0 for l in lengths):
# all samples are in the same modality
return get_length_grouped_indices(lengths, batch_size, world_size, generator=generator)
mm_indices, mm_lengths = zip(*[(i, l) for i, l in enumerate(lengths) if l > 0])
lang_indices, lang_lengths = zip(*[(i, -l) for i, l in enumerate(lengths) if l < 0])

assert len(mm_indices) > 0, "Should have at least one multimodal sample."
assert len(lang_indices) > 0, "Should have at least one language sample."

mm_shuffle = [mm_indices[i] for i in get_length_grouped_indices(mm_lengths, batch_size, world_size, generator=None)]
lang_shuffle = [lang_indices[i] for i in get_length_grouped_indices(lang_lengths, batch_size, world_size, generator=None)]
megabatch_size = world_size * batch_size
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