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	| import json | |
| import re | |
| import six | |
| from six.moves import range # pylint: disable=redefined-builtin | |
| PAD = "<pad>" | |
| EOS = "<EOS>" | |
| UNK = "<UNK>" | |
| SEG = "|" | |
| PUNCS = '!,.?;:' | |
| RESERVED_TOKENS = [PAD, EOS, UNK] | |
| NUM_RESERVED_TOKENS = len(RESERVED_TOKENS) | |
| PAD_ID = RESERVED_TOKENS.index(PAD) # Normally 0 | |
| EOS_ID = RESERVED_TOKENS.index(EOS) # Normally 1 | |
| UNK_ID = RESERVED_TOKENS.index(UNK) # Normally 2 | |
| if six.PY2: | |
| RESERVED_TOKENS_BYTES = RESERVED_TOKENS | |
| else: | |
| RESERVED_TOKENS_BYTES = [bytes(PAD, "ascii"), bytes(EOS, "ascii")] | |
| # Regular expression for unescaping token strings. | |
| # '\u' is converted to '_' | |
| # '\\' is converted to '\' | |
| # '\213;' is converted to unichr(213) | |
| _UNESCAPE_REGEX = re.compile(r"\\u|\\\\|\\([0-9]+);") | |
| _ESCAPE_CHARS = set(u"\\_u;0123456789") | |
| def strip_ids(ids, ids_to_strip): | |
| """Strip ids_to_strip from the end ids.""" | |
| ids = list(ids) | |
| while ids and ids[-1] in ids_to_strip: | |
| ids.pop() | |
| return ids | |
| class TextEncoder(object): | |
| """Base class for converting from ints to/from human readable strings.""" | |
| def __init__(self, num_reserved_ids=NUM_RESERVED_TOKENS): | |
| self._num_reserved_ids = num_reserved_ids | |
| def num_reserved_ids(self): | |
| return self._num_reserved_ids | |
| def encode(self, s): | |
| """Transform a human-readable string into a sequence of int ids. | |
| The ids should be in the range [num_reserved_ids, vocab_size). Ids [0, | |
| num_reserved_ids) are reserved. | |
| EOS is not appended. | |
| Args: | |
| s: human-readable string to be converted. | |
| Returns: | |
| ids: list of integers | |
| """ | |
| return [int(w) + self._num_reserved_ids for w in s.split()] | |
| def decode(self, ids, strip_extraneous=False): | |
| """Transform a sequence of int ids into a human-readable string. | |
| EOS is not expected in ids. | |
| Args: | |
| ids: list of integers to be converted. | |
| strip_extraneous: bool, whether to strip off extraneous tokens | |
| (EOS and PAD). | |
| Returns: | |
| s: human-readable string. | |
| """ | |
| if strip_extraneous: | |
| ids = strip_ids(ids, list(range(self._num_reserved_ids or 0))) | |
| return " ".join(self.decode_list(ids)) | |
| def decode_list(self, ids): | |
| """Transform a sequence of int ids into a their string versions. | |
| This method supports transforming individual input/output ids to their | |
| string versions so that sequence to/from text conversions can be visualized | |
| in a human readable format. | |
| Args: | |
| ids: list of integers to be converted. | |
| Returns: | |
| strs: list of human-readable string. | |
| """ | |
| decoded_ids = [] | |
| for id_ in ids: | |
| if 0 <= id_ < self._num_reserved_ids: | |
| decoded_ids.append(RESERVED_TOKENS[int(id_)]) | |
| else: | |
| decoded_ids.append(id_ - self._num_reserved_ids) | |
| return [str(d) for d in decoded_ids] | |
| def vocab_size(self): | |
| raise NotImplementedError() | |
| class TokenTextEncoder(TextEncoder): | |
| """Encoder based on a user-supplied vocabulary (file or list).""" | |
| def __init__(self, | |
| vocab_filename, | |
| reverse=False, | |
| vocab_list=None, | |
| replace_oov=None, | |
| num_reserved_ids=NUM_RESERVED_TOKENS): | |
| """Initialize from a file or list, one token per line. | |
| Handling of reserved tokens works as follows: | |
| - When initializing from a list, we add reserved tokens to the vocab. | |
| - When initializing from a file, we do not add reserved tokens to the vocab. | |
| - When saving vocab files, we save reserved tokens to the file. | |
| Args: | |
| vocab_filename: If not None, the full filename to read vocab from. If this | |
| is not None, then vocab_list should be None. | |
| reverse: Boolean indicating if tokens should be reversed during encoding | |
| and decoding. | |
| vocab_list: If not None, a list of elements of the vocabulary. If this is | |
| not None, then vocab_filename should be None. | |
| replace_oov: If not None, every out-of-vocabulary token seen when | |
| encoding will be replaced by this string (which must be in vocab). | |
| num_reserved_ids: Number of IDs to save for reserved tokens like <EOS>. | |
| """ | |
| super(TokenTextEncoder, self).__init__(num_reserved_ids=num_reserved_ids) | |
| self._reverse = reverse | |
| self._replace_oov = replace_oov | |
| if vocab_filename: | |
| self._init_vocab_from_file(vocab_filename) | |
| else: | |
| assert vocab_list is not None | |
| self._init_vocab_from_list(vocab_list) | |
| self.pad_index = self.token_to_id[PAD] | |
| self.eos_index = self.token_to_id[EOS] | |
| self.unk_index = self.token_to_id[UNK] | |
| self.seg_index = self.token_to_id[SEG] if SEG in self.token_to_id else self.eos_index | |
| def encode(self, s): | |
| """Converts a space-separated string of tokens to a list of ids.""" | |
| sentence = s | |
| tokens = sentence.strip().split() | |
| if self._replace_oov is not None: | |
| tokens = [t if t in self.token_to_id else self._replace_oov | |
| for t in tokens] | |
| ret = [self.token_to_id[tok] for tok in tokens] | |
| return ret[::-1] if self._reverse else ret | |
| def decode(self, ids, strip_eos=False, strip_padding=False): | |
| if strip_padding and self.pad() in list(ids): | |
| pad_pos = list(ids).index(self.pad()) | |
| ids = ids[:pad_pos] | |
| if strip_eos and self.eos() in list(ids): | |
| eos_pos = list(ids).index(self.eos()) | |
| ids = ids[:eos_pos] | |
| return " ".join(self.decode_list(ids)) | |
| def decode_list(self, ids): | |
| seq = reversed(ids) if self._reverse else ids | |
| return [self._safe_id_to_token(i) for i in seq] | |
| def vocab_size(self): | |
| return len(self.id_to_token) | |
| def __len__(self): | |
| return self.vocab_size | |
| def _safe_id_to_token(self, idx): | |
| return self.id_to_token.get(idx, "ID_%d" % idx) | |
| def _init_vocab_from_file(self, filename): | |
| """Load vocab from a file. | |
| Args: | |
| filename: The file to load vocabulary from. | |
| """ | |
| with open(filename) as f: | |
| tokens = [token.strip() for token in f.readlines()] | |
| def token_gen(): | |
| for token in tokens: | |
| yield token | |
| self._init_vocab(token_gen(), add_reserved_tokens=False) | |
| def _init_vocab_from_list(self, vocab_list): | |
| """Initialize tokens from a list of tokens. | |
| It is ok if reserved tokens appear in the vocab list. They will be | |
| removed. The set of tokens in vocab_list should be unique. | |
| Args: | |
| vocab_list: A list of tokens. | |
| """ | |
| def token_gen(): | |
| for token in vocab_list: | |
| if token not in RESERVED_TOKENS: | |
| yield token | |
| self._init_vocab(token_gen()) | |
| def _init_vocab(self, token_generator, add_reserved_tokens=True): | |
| """Initialize vocabulary with tokens from token_generator.""" | |
| self.id_to_token = {} | |
| non_reserved_start_index = 0 | |
| if add_reserved_tokens: | |
| self.id_to_token.update(enumerate(RESERVED_TOKENS)) | |
| non_reserved_start_index = len(RESERVED_TOKENS) | |
| self.id_to_token.update( | |
| enumerate(token_generator, start=non_reserved_start_index)) | |
| # _token_to_id is the reverse of _id_to_token | |
| self.token_to_id = dict((v, k) for k, v in six.iteritems(self.id_to_token)) | |
| def pad(self): | |
| return self.pad_index | |
| def eos(self): | |
| return self.eos_index | |
| def unk(self): | |
| return self.unk_index | |
| def seg(self): | |
| return self.seg_index | |
| def store_to_file(self, filename): | |
| """Write vocab file to disk. | |
| Vocab files have one token per line. The file ends in a newline. Reserved | |
| tokens are written to the vocab file as well. | |
| Args: | |
| filename: Full path of the file to store the vocab to. | |
| """ | |
| with open(filename, "w") as f: | |
| for i in range(len(self.id_to_token)): | |
| f.write(self.id_to_token[i] + "\n") | |
| def sil_phonemes(self): | |
| return [p for p in self.id_to_token.values() if is_sil_phoneme(p)] | |
| def build_token_encoder(token_list_file): | |
| token_list = json.load(open(token_list_file)) | |
| return TokenTextEncoder(None, vocab_list=token_list, replace_oov='<UNK>') | |
| def is_sil_phoneme(p): | |
| return p == '' or not p[0].isalpha() | |
