AudioGPT / NeuralSeq /utils /text_encoder.py
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import re
import six
from six.moves import range # pylint: disable=redefined-builtin
PAD = "<pad>"
EOS = "<EOS>"
UNK = "<UNK>"
SEG = "|"
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
@property
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]
@property
def vocab_size(self):
raise NotImplementedError()
class ByteTextEncoder(TextEncoder):
"""Encodes each byte to an id. For 8-bit strings only."""
def encode(self, s):
numres = self._num_reserved_ids
if six.PY2:
if isinstance(s, unicode):
s = s.encode("utf-8")
return [ord(c) + numres for c in s]
# Python3: explicitly convert to UTF-8
return [c + numres for c in s.encode("utf-8")]
def decode(self, ids, strip_extraneous=False):
if strip_extraneous:
ids = strip_ids(ids, list(range(self._num_reserved_ids or 0)))
numres = self._num_reserved_ids
decoded_ids = []
int2byte = six.int2byte
for id_ in ids:
if 0 <= id_ < numres:
decoded_ids.append(RESERVED_TOKENS_BYTES[int(id_)])
else:
decoded_ids.append(int2byte(id_ - numres))
if six.PY2:
return "".join(decoded_ids)
# Python3: join byte arrays and then decode string
return b"".join(decoded_ids).decode("utf-8", "replace")
def decode_list(self, ids):
numres = self._num_reserved_ids
decoded_ids = []
int2byte = six.int2byte
for id_ in ids:
if 0 <= id_ < numres:
decoded_ids.append(RESERVED_TOKENS_BYTES[int(id_)])
else:
decoded_ids.append(int2byte(id_ - numres))
# Python3: join byte arrays and then decode string
return decoded_ids
@property
def vocab_size(self):
return 2**8 + self._num_reserved_ids
class ByteTextEncoderWithEos(ByteTextEncoder):
"""Encodes each byte to an id and appends the EOS token."""
def encode(self, s):
return super(ByteTextEncoderWithEos, self).encode(s) + [EOS_ID]
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]
@property
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 not p[0].isalpha()]