def feature_encoders(self, data_dir):
# This vocab file must be present within the data directory.
vocab_filename = os.path.join(data_dir, "charset_size134.txt")
return {
"inputs": text_encoder.ImageEncoder(),
"targets": text_encoder.SubwordTextEncoder(vocab_filename)
}
def feature_encoders(self, data_dir):
if self.is_character_level:
encoder = text_encoder.ByteTextEncoder()
else:
vocab_filename = os.path.join(data_dir, self.vocab_name)
encoder = text_encoder.TokenTextEncoder(vocab_filename)
input_encoder = text_encoder.ImageEncoder()
return {"inputs": input_encoder, "targets": encoder}
def feature_encoders(self, data_dir):
if self.is_character_level:
encoder = text_encoder.ByteTextEncoder()
else:
vocab_filename = os.path.join(
data_dir, self.vocab_problem.vocab_filename)
encoder = text_encoder.SubwordTextEncoder(vocab_filename)
input_encoder = text_encoder.ImageEncoder(channels=self.num_channels)
return {"inputs": input_encoder, "targets": encoder}
def feature_encoders(self, data_dir):
if self.is_character_level:
encoder = text_encoder.ByteTextEncoder()
else:
vocab_filename = os.path.join(
data_dir, "vocab.ende.%d" % self.targeted_vocab_size)
encoder = text_encoder.SubwordTextEncoder(vocab_filename)
input_encoder = text_encoder.ImageEncoder()
return {"inputs": input_encoder, "targets": encoder}
def feature_encoders(self, data_dir):
input_encoder = text_encoder.ImageEncoder(channels=self.num_channels)
vocab_file = os.path.join(data_dir, self.vocab_filename)
question_encoder = text_encoder.TokenTextEncoder(
vocab_file, replace_oov="UNK")
label_file = os.path.join(data_dir, self.label_filename)
target_encoder = text_encoder.ClassLabelEncoder(
class_labels_fname=label_file)
return {"inputs": input_encoder,
"question": question_encoder,
"targets": target_encoder}
def feature_encoders(self, data_dir):
del data_dir
return {
"inputs": text_encoder.ImageEncoder(channels=self.num_channels),
"targets": text_encoder.ImageEncoder(channels=self.num_channels)
}
def feature_encoders(self, data_dir):
del data_dir
return {
"inputs": text_encoder.ImageEncoder(),
"targets": text_encoder.ClassLabelEncoder(self.class_labels)
}
