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from score_acculumator import ScoreAccumulator
import argparse, json, os
def main(filepath, measures, writeback=False, outpath=""):
"""
Evaluate a model using specified measures given a filepath to database of songs.
Database must be formatted as follows:
[
#dict 1 for song 1
{
"id": (int) ...,
"prompt": (str) ..., #optional
"model_response": (str) ...,
"target_response": (str) ... #optional
},
#dict 2 for song 2
{
" "
},
.
.
.
]
Parameters
----------
filepath : str
path to database .json file
measures : list
list of measures to evaluate model outputs, from {'diversity','meter','syllable'}
writeback : bool, optional
Whether to write evaluation scores to filepath or to output, by default False
outpath : str, optional
path to output .json file if writeback is False, by default ""
Raises
------
FileNotFoundError
"""
# read file
if os.path.exists(filepath):
with open(filepath, "r") as f:
database = json.load(f)
else:
raise FileNotFoundError(f"No such file exists: {filepath}")
if not writeback:
if not os.path.exists(outpath):
raise FileNotFoundError(f"No such file exists: {outpath}")
else:
outpath = filepath
# evaluate for measures
accumulator = ScoreAccumulator(
measures=measures,
require_prompt="prompt" in database[0],
require_target="target_response" in database[0],
)
accumulator.score_all_songs(database)
# print total scores
for measure in measures:
pred_score = accumulator.get_total_pred_score(measure)
target_score = accumulator.get_total_target_score(measure)
print(f"Score: pred {pred_score:2f}, target {target_score:2f} : ({measure})")
# save evaluation
out_database = []
for id, song_dict in accumulator._database.items():
song_dict["id"] = int(id)
out_database.append(song_dict)
with open(filepath, "w") as f:
f.write(json.dumps(out_database, indent=2, separators=[",", ":"]))
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Evaluate a model given a filepath to a database of songs."
)
parser.add_argument(
"filepath", type=str, help="The path to the file to be processed"
)
parser.add_argument(
"--measures",
default=["diversity", "meter", "syllable"],
nargs="+",
help="List of measures to evaluate. From {'diversity','meter','syllable'}",
)
parser.add_argument(
"--writeback",
type=bool,
default=True,
help="Write evaluation scores back to the same dict or create a new one",
)
parser.add_argument(
"--output",
default="",
type=str,
help="The path to the write output scores if writeback is false",
)
args = parser.parse_args()
main(args.filepath, args.measures, args.writeback, args.output)
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