jiangzhs/OpenCompass
1
0
Fork 0
mirror of https://github.com/open-compass/opencompass.git synced 2025-05-30 16:03:24 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

[Fix] Fix bugs of multiple rounds of inference when using mm_eval (#201)

Browse Source
This commit is contained in:
Yike Yuan 2023-08-16 11:15:11 +08:00 committed by GitHub
parent 4fc1701209
commit 3a46b6c64f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 6 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
opencompass/tasks/mm_infer.py
View File

@ -6,6 +6,7 @@ import random
import time import time
from typing import List, Sequence from typing import List, Sequence
import mmengine
import torch import torch
import torch.distributed as dist import torch.distributed as dist
from mmengine.config import Config, ConfigDict from mmengine.config import Config, ConfigDict
@ -75,8 +76,8 @@ class MultimodalInferTask:
dataset_name = self.dataloader['dataset']['type'] dataset_name = self.dataloader['dataset']['type']
evaluator_name = self.evaluator[0]['type'] evaluator_name = self.evaluator[0]['type']
return osp.join(model_name, return osp.join(self.cfg.work_dir, model_name, dataset_name,
f'{dataset_name}-{evaluator_name}.{file_extension}') f'{evaluator_name}.{file_extension}')
def get_output_paths(self, file_extension: str = 'json') -> List[str]: def get_output_paths(self, file_extension: str = 'json') -> List[str]:
"""Get the path to the output file. """Get the path to the output file.
@ -90,7 +91,7 @@ class MultimodalInferTask:
evaluator_name = self.evaluator[0]['type'] evaluator_name = self.evaluator[0]['type']
return [ return [
osp.join(model_name, dataset_name, osp.join(self.cfg.work_dir, model_name, dataset_name,
f'{evaluator_name}.{file_extension}') f'{evaluator_name}.{file_extension}')
] ]
@ -134,7 +135,8 @@ class MultimodalInferTask:
evaluator.process(data_samples) evaluator.process(data_samples)
metrics = evaluator.evaluate(len(dataloader.dataset)) metrics = evaluator.evaluate(len(dataloader.dataset))
metrics_file = osp.join(cfg.work_dir, 'res.log') metrics_file = self.get_output_paths()[0]
mmengine.mkdir_or_exist(osp.split(metrics_file)[0])
with open(metrics_file, 'w') as f: with open(metrics_file, 'w') as f:
json.dump(metrics, f) json.dump(metrics, f)