c54c430da19670cb030e32558b6810d04767dd99,allennlp/nn/util.py,,sort_batch_by_length,#Any#Any#,26

Before Change

        Indices into the sorted_tensor such that ``sorted_tensor[restoration_indices] == original_tensor``
    
    sorted_sequence_lengths, permutation_index = sequence_lengths.sort(0, descending=True)
    sorted_tensor = tensor[permutation_index]
    // This is the equivalent of zipping with index, sorting by the original
    // sequence lengths and returning the now sorted indices.
    index_range = torch.range(0, len(sequence_lengths) - 1).long()
    _, reverse_mapping = permutation_index.sort(0, descending=False)

After Change

        ``sorted_tensor.index_select(0, restoration_indices) == original_tensor``
    

    if not isinstance(tensor, Variable) or not isinstance(sequence_lengths, Variable):
        raise ConfigurationError("Both the tensor and sequence lengths must be torch.autograd.Variables.")

    sorted_sequence_lengths, permutation_index = sequence_lengths.sort(0, descending=True)
    sorted_tensor = tensor.index_select(0, permutation_index)
    // This is the equivalent of zipping with index, sorting by the original
    // sequence lengths and returning the now sorted indices.

Instances