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) }