def _load_pairings_file(self):
"""
Build the pairings file for the two models.
If a pairings file already exists, we ask the user whether they would like to
overwrite the pairings file.
"""
pairings_filepath = get_hashed_combo_path(
root_dir=self.fast_acute_args.root_dir,
subdir='pairings_files',
task=self.task,
combos=self.combos,
)
if not os.path.exists(pairings_filepath):
self._build_pairings_file(pairings_filepath)
else:
modify_time = os.path.getmtime(pairings_filepath)
self._print_progress(
f'Pairings already exist {pairings_filepath}. Last modified {time.ctime(modify_time)}'
)
if not self.fast_acute_args.use_existing_self_chat_files:
answer = ''
while answer.lower().strip() != 'y' and answer.lower().strip(
) != 'o':
answer = input('Enter y to use, o to overwrite:')
if answer.lower().strip() == 'o':
self._build_pairings_file(pairings_filepath)
self._print_progress(f'loading pairings file from {pairings_filepath}')
self.pairings_filepath = pairings_filepath
def analyze_results(self, args: Optional[str] = None):
"""
Analyze results of ACUTE Eval run, using the optional input args.
Save results to appropriate filepath.
"""
self._print_progress(f'Analyzing Results for run id {self.run_id}')
parser = analysis_setup_args()
if args is not None:
arg_string = args.split()
else:
arg_string = []
opt = parser.parse_args(arg_string)
today = datetime.date.today().isoformat()
self.results_path = get_hashed_combo_path(
root_dir=self.fast_acute_args.root_dir,
subdir=f'acute_results/{today}/',
task=self.task,
combos=self.combos,
)
opt.update({
'model_strings': ','.join(self.models),
'run_ids': self.run_id,
'root_dir': self.fast_acute_args.root_dir,
'outdir': self.results_path,
'task': self.task,
})
analyzer = self.ANALYZER(opt)
self.results = analyzer.get_matchup_totals_with_significance()
analyzer.save_results()
self._print_progress(f'ACUTE Results: {self.results}')
self._print_progress(f'ACUTE results saved to {self.results_path}')
def _load_pairing_files(self):
df = self.dataframe
if not os.path.exists(self.pairings_filepath):
print('No valid pairings filepath was passed in: will extract likely path.')
self.pairings_filepath = get_hashed_combo_path(
root_dir=self.root_dir,
subdir='pairings_files',
task=self.task,
combos=self.combos,
)
if not os.path.exists(self.pairings_filepath):
print(
f'WARNING: Pairings filepath {self.pairings_filepath} could not be found.'
)
self.pairings_filepath = os.path.join(
self.root_dir,
'pairings_files',
hashlib.sha1(
'___vs___'.join(
[f"{m}.{'q'.replace(':', '_')}" for m in self.models]
).encode('utf-8')
).hexdigest()[:10],
)
if not os.path.exists(self.pairings_filepath):
# For backward compatibility
print(
f'WARNING: Pairings filepath {self.pairings_filepath} could not be found.'
)
self.pairings_filepath = os.path.join(
self.root_dir,
'pairings_files',
'___vs___'.join(
[f"{m}.{self.task.replace(':', '_')}" for m in self.models]
),
)
if not os.path.exists(self.pairings_filepath):
print(
f'NOTE: Pairings filepath {self.pairings_filepath} could not be found!'
)
return
self.pairings = []
with open(self.pairings_filepath, 'r') as f:
for line in f:
pair = json.loads(line)
model1, model2 = pair['speakers_to_eval']
pair[model1] = pair['dialogue_dicts'][0]
pair[model2] = pair['dialogue_dicts'][1]
del pair['dialogue_dicts']
self.pairings.append(pair)
self.pairs_to_eval = [self.pairings[i] for i in df.pairing_id.values.tolist()]
# Build dialogue_ids => dialogue mappings
winner_dialogues = []
loser_dialogues = []
for i, (_, row) in enumerate(df.iterrows()):
winner = row['winner']
loser = row['loser']
winner_dialogues.append(self.pairs_to_eval[i][winner])
loser_dialogues.append(self.pairs_to_eval[i][loser])
df['pairs_to_eval'] = pd.Series(self.pairs_to_eval, index=df.index)
df['winner_dialogue'] = pd.Series(winner_dialogues, index=df.index)
df['loser_dialogue'] = pd.Series(loser_dialogues, index=df.index)
self.dataframe = df