Python tokenization.convert_to_unicode方法代碼示例

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def _create_examples(self, lines, set_type):
        """Creates examples for the training and dev sets."""
        examples = []
        for (i, line) in enumerate(lines):
            if i == 0:
                continue
            guid = "%s-%s" % (set_type, tokenization.convert_to_unicode(line[0]))
            text_a = tokenization.convert_to_unicode(line[8])
            text_b = tokenization.convert_to_unicode(line[9])
            if set_type == "test":
                label = "contradiction"
            else:
                label = tokenization.convert_to_unicode(line[-1])
            examples.append(
                InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
        return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_train_examples(self, data_dir):
        # 數據可以保存在多個文件中，命名格式為train*.txt
        file_list = []
        for file in os.listdir(data_dir):
            if 'train' in os.path.splitext(file)[0]:
                file_list.append(file)
        file_path = [os.path.join(data_dir, file) for file in file_list]
        i = 0
        example = []
        for file in file_path:
            with open(file, 'r') as f:
                reader = f.readlines()
            for line in reader:
                guid = 'train-%d' % i
                i += 1
                split_line = line.strip().split('\t')
                # 數據清洗
                if len(split_line) != 4:
                    print("髒數據：",split_line)
                    continue
                text_a = tokenization.convert_to_unicode(split_line[1])
                text_b = tokenization.convert_to_unicode(split_line[2])
                label = str(split_line[3])
                example.append(InputExample(guid, text_a, text_b, label))
        return example 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def read_examples(input_file):
  """Read a list of `InputExample`s from an input file."""
  examples = []
  unique_id = 0
  with tf.gfile.GFile(input_file, "r") as reader:
    while True:
      line = tokenization.convert_to_unicode(reader.readline())
      if not line:
        break
      line = line.strip()
      text_a = None
      text_b = None
      m = re.match(r"^(.*) \|\|\| (.*)$", line)
      if m is None:
        text_a = line
      else:
        text_a = m.group(1)
        text_b = m.group(2)
      examples.append(
          InputExample(unique_id=unique_id, text_a=text_a, text_b=text_b))
      unique_id += 1
  return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_train_examples(self, data_dir):
    """See base class."""
    lines = self._read_tsv(
        os.path.join(data_dir, "multinli",
                     "multinli.train.%s.tsv" % self.language))
    examples = []
    for (i, line) in enumerate(lines):
      if i == 0:
        continue
      guid = "train-%d" % (i)
      text_a = tokenization.convert_to_unicode(line[0])
      text_b = tokenization.convert_to_unicode(line[1])
      label = tokenization.convert_to_unicode(line[2])
      if label == tokenization.convert_to_unicode("contradictory"):
        label = tokenization.convert_to_unicode("contradiction")
      examples.append(
          InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_dev_examples(self, data_dir):
    """See base class."""
    lines = self._read_tsv(os.path.join(data_dir, "xnli.dev.tsv"))
    examples = []
    for (i, line) in enumerate(lines):
      if i == 0:
        continue
      guid = "dev-%d" % (i)
      language = tokenization.convert_to_unicode(line[0])
      if language != tokenization.convert_to_unicode(self.language):
        continue
      text_a = tokenization.convert_to_unicode(line[6])
      text_b = tokenization.convert_to_unicode(line[7])
      label = tokenization.convert_to_unicode(line[1])
      examples.append(
          InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def _create_examples(self, lines, set_type):
    """Creates examples for the training and dev sets."""
    examples = []
    for (i, line) in enumerate(lines):
      if i == 0:
        continue
      guid = "%s-%s" % (set_type, tokenization.convert_to_unicode(line[0]))
      text_a = tokenization.convert_to_unicode(line[8])
      text_b = tokenization.convert_to_unicode(line[9])
      if set_type == "test":
        label = "contradiction"
      else:
        label = tokenization.convert_to_unicode(line[-1])
      examples.append(
          InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_train_examples(self, data_dir):
    """See base class."""
    lines = self._read_csv(os.path.join(data_dir, "train.csv"))
    examples = []
    if self.swap_input:
        for (i, line) in enumerate(lines):
          guid = "train-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[1])
          text_b = tokenization.convert_to_unicode(line[0])
          label = tokenization.convert_to_unicode(line[2])
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    else:
        for (i, line) in enumerate(lines):
          guid = "train-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[0])
          text_b = tokenization.convert_to_unicode(line[1])
          label = tokenization.convert_to_unicode(line[2])
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_test_examples(self, data_dir):
    """See base class."""
    lines = self._read_csv(os.path.join(data_dir, "test.csv"), istrain=False)
    examples = []
    if self.swap_input:
        for (i, line) in enumerate(lines):
          guid = "test-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[1])
          text_b = tokenization.convert_to_unicode(line[0])
          label = "unrelated"
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    else:
        for (i, line) in enumerate(lines):
          guid = "test-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[0])
          text_b = tokenization.convert_to_unicode(line[1])
          label = "unrelated"
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_train_examples(self, data_dir):
    """See base class."""
    lines = self._read_csv(os.path.join(data_dir, "train.csv"))
    X = np.loadtxt(FLAGS.extra_train_tensor)
    examples = []
    if self.swap_input:
        for (i, line) in enumerate(lines):
          guid = "train-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[1])
          text_b = tokenization.convert_to_unicode(line[0])
          label = tokenization.convert_to_unicode(line[2])
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label, extra_feats=list(X[i])))
    else:
        for (i, line) in enumerate(lines):
          guid = "train-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[0])
          text_b = tokenization.convert_to_unicode(line[1])
          label = tokenization.convert_to_unicode(line[2])
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label, extra_feats=list(X[i])))
    return examples 

# 需要導入模塊: import tokenization [as 別名]
# 或者: from tokenization import convert_to_unicode [as 別名]
def get_test_examples(self, data_dir):
    """See base class."""
    lines = self._read_csv(os.path.join(data_dir, "test.csv"), istrain=False)
    X = np.loadtxt(FLAGS.extra_test_tensor)
    examples = []
    if self.swap_input:
        for (i, line) in enumerate(lines):
          guid = "test-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[1])
          text_b = tokenization.convert_to_unicode(line[0])
          label = "unrelated"
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label, extra_feats=list(X[i])))
    else:
        for (i, line) in enumerate(lines):
          guid = "test-%d" % (i)
          text_a = tokenization.convert_to_unicode(line[0])
          text_b = tokenization.convert_to_unicode(line[1])
          label = "unrelated"
          examples.append(
              InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label, extra_feats=list(X[i])))
    return examples