DialogZoo / src /DCRG.py
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data preprocessing update
a6326c7
import sys
sys.path.append("modules/preprocess")
from preprocessor.SerialPreprocessor import SerialConfig, SerialPreprocessor
from const import (
DIALOGUE_CONTEXT_TO_RESPONSE_GENERATION,
DOCUMENT_GROUNDED_CONVERSATION,
MULTI_REF_SEP,
)
from preprocessor.prompt_funcs import const_prompt_func_wrapper
from preprocessor.knowledge_funcs import (
extract_dialogue_knowledge_wrapper,
origin_knowledge,
None_knowledge,
extract_kg_knowledge_wrapper,
extract_turn_knowledge_wrapper,
)
from preprocessor.label_funs import (
extract_turn_utterance,
)
import sys
if __name__ == "__main__":
input_data_path = sys.argv[1]
output_data_path = sys.argv[2]
TASK = DOCUMENT_GROUNDED_CONVERSATION
if len(sys.argv) <= 3:
based_on = "dialogue"
else:
based_on = sys.argv[3]
if len(sys.argv) < 5:
if based_on == "turn-document":
serial_proc = SerialPreprocessor(
SerialConfig(
input_data_path,
output_data_path,
TASK,
logger_name=TASK,
task_bos_token=f"[{TASK}]",
prompt_func=const_prompt_func_wrapper(
"Response based on the dialogue context and given knowledge"
),
# knowledge_func=extract_kg_knowledge_wrapper(": ", " | ", "; ", " "),
# knowledge_func=extract_dialogue_knowledge_wrapper(": ", " | ", ", "),
# knowledge_func=None_knowledge,
knowledge_func=origin_knowledge,
turn_knowledge_func=extract_turn_knowledge_wrapper(
": ", " | ", ", "
),
label_func=extract_turn_utterance,
roles_to_build_example=[["user1"], ["user2"]],
# dev_and_test_roles_to_build_example=[["user2"]],
roles_in_history=None,
multi_ref_sep=None,
)
)
elif based_on == "document":
serial_proc = SerialPreprocessor(
SerialConfig(
input_data_path,
output_data_path,
TASK,
logger_name=TASK,
task_bos_token=f"[{TASK}]",
prompt_func=const_prompt_func_wrapper(
"Response based on the dialogue context and given knowledge"
),
# knowledge_func=extract_kg_knowledge_wrapper(": ", " | ", "; ", " "),
knowledge_func=extract_dialogue_knowledge_wrapper(
": ", " | ", ", "
),
# knowledge_func=None_knowledge,
# knowledge_func=origin_knowledge,
label_func=extract_turn_utterance,
roles_to_build_example=[
["third-person"],
["Listener"],
["Speaker"],
],
dev_and_test_roles_to_build_example=[
["third-person"],
["Listener"],
],
)
)
elif based_on == "None":
serial_proc = SerialPreprocessor(
SerialConfig(
input_data_path,
output_data_path,
TASK,
logger_name=TASK,
task_bos_token=f"[{TASK}]",
prompt_func=const_prompt_func_wrapper(
"Response based on the dialogue context and given knowledge"
),
knowledge_func=None_knowledge,
label_func=extract_turn_utterance,
roles_to_build_example=[["SYSTEM"]],
)
)
else:
serial_proc = SerialPreprocessor(
SerialConfig(
input_data_path,
output_data_path,
TASK,
logger_name=TASK,
task_bos_token=f"[{TASK}]",
prompt_func=const_prompt_func_wrapper(
"Response based on the dialogue context and given knowledge"
),
knowledge_func=extract_kg_knowledge_wrapper(": ", " | ", "; ", " "),
# knowledge_func=extract_dialogue_knowledge_wrapper(": ", " | ", ", "),
# knowledge_func=None_knowledge,
label_func=extract_turn_utterance,
roles_to_build_example=[["SYSTEM"], ["USER"]],
dev_and_test_roles_to_build_example=[["SYSTEM"]],
)
)
else:
serial_proc = SerialPreprocessor(
SerialConfig(
input_data_path,
output_data_path,
TASK,
logger_name=TASK,
task_bos_token=f"[{TASK}]",
prompt_func=const_prompt_func_wrapper(
"Response based on the dialogue context and given knowledge"
),
# knowledge_func=extract_kg_knowledge_wrapper(": ", " | ", "; ", " "),
knowledge_func=extract_dialogue_knowledge_wrapper(": ", " | ", ", "),
label_func=extract_turn_utterance,
roles_to_build_example=[["SYSTEM"]],
roles_in_history=[["USER"]],
multi_ref_sep=MULTI_REF_SEP,
)
)
serial_proc.launch()