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| | | from typing import Any, Dict, Iterable, List, NamedTuple, Set, Tuple, Union |
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| | | |
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| | | import re |
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| | | import torch |
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| | | import numpy as np |
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| | | import yaml |
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| | | try: |
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| | |
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| | | n_batch = len(xs) |
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| | | if max_len is None: |
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| | | max_len = max(x.size(0) for x in xs) |
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| | | pad = xs[0].new(n_batch, max_len, *xs[0].size()[1:]).fill_(pad_value) |
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| | | |
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| | | # pad = xs[0].new(n_batch, max_len, *xs[0].size()[1:]).fill_(pad_value) |
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| | | # numpy format |
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| | | pad = np.zeros((n_batch, max_len)).astype(np.int32) |
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| | | for i in range(n_batch): |
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| | | pad[i, : xs[i].size(0)] = xs[i] |
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| | | pad[i, : xs[i].shape[0]] = xs[i] |
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| | | |
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| | | return pad |
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| | | |
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| | | |
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| | | ''' |
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| | | def make_pad_mask(lengths, xs=None, length_dim=-1, maxlen=None): |
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| | | if length_dim == 0: |
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| | | raise ValueError("length_dim cannot be 0: {}".format(length_dim)) |
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| | |
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| | | ) |
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| | | mask = mask[ind].expand_as(xs).to(xs.device) |
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| | | return mask |
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| | | |
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| | | ''' |
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| | | |
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| | | class TokenIDConverter(): |
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| | | def __init__(self, token_list: Union[List, str], |
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