internal merge

PiperOrigin-RevId: 160018490

Author: Ryan Sepassi

tensor2tensor/data_generators/generator_utils.py

@@ -28,6 +28,7 @@
 
 import six
 from six.moves import xrange  # pylint: disable=redefined-builtin
+import six.moves.urllib_request
 
 from tensor2tensor.data_generators.text_encoder import SubwordTextEncoder
 from tensor2tensor.data_generators.tokenizer import Tokenizer

tensor2tensor/data_generators/image.py

@@ -18,7 +18,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import cPickle
 import gzip
 import io
 import json
@@ -30,6 +29,7 @@
 # Dependency imports
 
 import numpy as np
+from six.moves import cPickle
 from six.moves import xrange  # pylint: disable=redefined-builtin
 from six.moves import zip  # pylint: disable=redefined-builtin
 from tensor2tensor.data_generators import generator_utils

tensor2tensor/data_generators/text_encoder.py

@@ -23,6 +23,8 @@
 from __future__ import division
 from __future__ import print_function
 
+from collections import defaultdict
+
 # Dependency imports
 
 import six
@@ -35,6 +37,10 @@
 PAD = '<pad>'
 EOS = '<EOS>'
 RESERVED_TOKENS = [PAD, EOS]
+if six.PY2:
+  RESERVED_TOKENS_BYTES = RESERVED_TOKENS
+else:
+  RESERVED_TOKENS_BYTES = [bytes(PAD, 'ascii'), bytes(EOS, 'ascii')]
 
 
 class TextEncoder(object):
@@ -87,17 +93,25 @@ class ByteTextEncoder(TextEncoder):
   """Encodes each byte to an id. For 8-bit strings only."""
 
   def encode(self, s):
-    return [ord(c) + self._num_reserved_ids for c in s]
+    numres = self._num_reserved_ids
+    if six.PY2:
+      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):
+    numres = self._num_reserved_ids
     decoded_ids = []
+    int2byte = six.int2byte
     for id_ in ids:
-      if 0 <= id_ < self._num_reserved_ids:
-        decoded_ids.append(RESERVED_TOKENS[int(id_)])
+      if 0 <= id_ < numres:
+        decoded_ids.append(RESERVED_TOKENS_BYTES[int(id_)])
       else:
-        decoded_ids.append(chr(id_))
-
-    return ''.join(decoded_ids)
+        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')
 
   @property
   def vocab_size(self):
@@ -111,20 +125,16 @@ def __init__(self, vocab_filename, reverse=False, num_reserved_ids=2):
     """Initialize from a file, one token per line."""
     super(TokenTextEncoder, self).__init__(num_reserved_ids=num_reserved_ids)
     self._reverse = reverse
-    if vocab_filename is not None:
-      self._load_vocab_from_file(vocab_filename)
+    self._load_vocab_from_file(vocab_filename)
 
   def encode(self, sentence):
     """Converts a space-separated string of tokens to a list of ids."""
     ret = [self._token_to_id[tok] for tok in sentence.strip().split()]
-    if self._reverse:
-      ret = ret[::-1]
-    return ret
+    return ret[::-1] if self._reverse else ret
 
   def decode(self, ids):
-    if self._reverse:
-      ids = ids[::-1]
-    return ' '.join([self._safe_id_to_token(i) for i in ids])
+    seq = reversed(ids) if self._reverse else ids
+    return ' '.join([self._safe_id_to_token(i) for i in seq])
 
   @property
   def vocab_size(self):
@@ -243,15 +253,22 @@ def _escaped_token_to_subtokens(self, escaped_token):
     """
     ret = []
     pos = 0
-    while pos < len(escaped_token):
-      end = len(escaped_token)
-      while True:
+    lesc = len(escaped_token)
+    while pos < lesc:
+      end = lesc
+      while end > pos:
         subtoken = self._subtoken_string_to_id.get(escaped_token[pos:end], -1)
         if subtoken != -1:
           break
         end -= 1
       ret.append(subtoken)
-      pos = end
+      if end > pos:
+        pos = end
+      else:
+        # This kinda should not happen, but it does. Cop out by skipping the
+        # nonexistent subtoken from the returned list.
+        # print("Unable to find subtoken in string '{0}'".format(escaped_token))
+        pos += 1
     return ret
 
   @classmethod
@@ -322,13 +339,13 @@ def build_from_token_counts(self,
     # then count the resulting potential subtokens, keeping the ones
     # with high enough counts for our new vocabulary.
     for i in xrange(num_iterations):
-      counts = {}
+      counts = defaultdict(int)
       for token, count in six.iteritems(token_counts):
         escaped_token = self._escape_token(token)
         # we will count all tails of the escaped_token, starting from boundaries
         # determined by our current segmentation.
         if i == 0:
-          starts = list(range(len(escaped_token)))
+          starts = xrange(len(escaped_token))
         else:
           subtokens = self._escaped_token_to_subtokens(escaped_token)
           pos = 0
@@ -337,31 +354,33 @@ def build_from_token_counts(self,
             starts.append(pos)
             pos += len(self.subtoken_to_subtoken_string(subtoken))
         for start in starts:
-          for end in xrange(start + 1, len(escaped_token) + 1):
+          for end in xrange(start + 1, len(escaped_token)):
             subtoken_string = escaped_token[start:end]
-            counts[subtoken_string] = counts.get(subtoken_string, 0) + count
+            counts[subtoken_string] += count
       # array of lists of candidate subtoken strings, by length
       len_to_subtoken_strings = []
       for subtoken_string, count in six.iteritems(counts):
-        if count < min_count or len(subtoken_string) <= 1:
+        lsub = len(subtoken_string)
+        # all subtoken strings of length 1 are included regardless of count
+        if count < min_count and lsub != 1:
           continue
-        while len(len_to_subtoken_strings) <= len(subtoken_string):
+        while len(len_to_subtoken_strings) <= lsub:
           len_to_subtoken_strings.append([])
-        len_to_subtoken_strings[len(subtoken_string)].append(subtoken_string)
+        len_to_subtoken_strings[lsub].append(subtoken_string)
       new_subtoken_strings = []
       # consider the candidates longest to shortest, so that if we accept
       # a longer subtoken string, we can decrement the counts of its prefixes.
       for subtoken_strings in len_to_subtoken_strings[::-1]:
         for subtoken_string in subtoken_strings:
           count = counts[subtoken_string]
-          if count < min_count:
+          if count < min_count and len(subtoken_string) != 1:
+            # subtoken strings of length 1 are included regardless of count
             continue
           new_subtoken_strings.append((-count, subtoken_string))
           for l in xrange(1, len(subtoken_string)):
             counts[subtoken_string[:l]] -= count
-      # make sure we have all single characters.
-      new_subtoken_strings.extend([(-counts.get(chr(i), 0), chr(i))
-                                   for i in xrange(2**8)])
+      # Make sure to include the underscore as a subtoken string
+      new_subtoken_strings.append((0, '_'))
       new_subtoken_strings.sort()
       self._init_from_list([''] * self._num_reserved_ids +
                            [p[1] for p in new_subtoken_strings])
@@ -390,13 +409,19 @@ def _load_from_file(self, filename):
     subtoken_strings = []
     with tf.gfile.Open(filename) as f:
       for line in f:
-        subtoken_strings.append(line.strip()[1:-1].decode('string-escape'))
+        if six.PY2:
+          subtoken_strings.append(line.strip()[1:-1].decode('string-escape'))
+        else:
+          subtoken_strings.append(line.strip()[1:-1])
     self._init_from_list(subtoken_strings)
 
   def _store_to_file(self, filename):
     with tf.gfile.Open(filename, 'w') as f:
       for subtoken_string in self._all_subtoken_strings:
-        f.write('\'' + subtoken_string.encode('string-escape') + '\'\n')
+        if six.PY2:
+          f.write('\'' + subtoken_string.encode('string-escape') + '\'\n')
+        else:
+          f.write('\'' + subtoken_string + '\'\n')
 
   def _escape_token(self, token):
     r"""Translate '\'->'\\' and '_'->'\u', then append '_'.

tensor2tensor/data_generators/tokenizer.py

@@ -45,7 +45,7 @@
 from __future__ import division
 from __future__ import print_function
 
-import array
+from collections import defaultdict
 import string
 
 # Dependency imports
@@ -57,17 +57,10 @@ class Tokenizer(object):
   """Vocab for breaking words into wordpieces.
   """
 
-  def __init__(self):
-    self._separator_chars = string.punctuation + string.whitespace
-    self._separator_char_mask = array.array(
-        "l", [chr(i) in self._separator_chars for i in xrange(256)])
-    self.token_counts = dict()
+  _SEPARATOR_CHAR_SET = set(string.punctuation + string.whitespace)
 
-  def _increment_token_count(self, token):
-    if token in self.token_counts:
-      self.token_counts[token] += 1
-    else:
-      self.token_counts[token] = 1
+  def __init__(self):
+    self.token_counts = defaultdict(int)
 
   def encode(self, raw_text):
     """Encode a raw string as a list of tokens.
@@ -87,11 +80,11 @@ def encode(self, raw_text):
         token = raw_text[token_start:pos]
         if token != " " or token_start == 0:
           ret.append(token)
-          self._increment_token_count(token)
+          self.token_counts[token] += 1
         token_start = pos
     final_token = raw_text[token_start:]
     ret.append(final_token)
-    self._increment_token_count(final_token)
+    self.token_counts[final_token] += 1
     return ret
 
   def decode(self, tokens):
@@ -111,7 +104,7 @@ def decode(self, tokens):
     return ret
 
   def _is_separator_char(self, c):
-    return self._separator_char_mask[ord(c)]
+    return c in self._SEPARATOR_CHAR_SET
 
   def _is_word_char(self, c):
-    return not self._is_separator_char(c)
+    return c not in self._SEPARATOR_CHAR_SET