mirror of
https://github.com/open-compass/opencompass.git
synced 2025-05-30 16:03:24 +08:00
78df9bd0cb
* [Feature]: Refactor class name * [Feature]: Add minigpt-4 coco caption * [Feature]: Update minigpt-4 coco caption * [Feature]: Add MiniGPT-4 ScienceQA * [Feature]: Add minigpt-4 vqav2 * [Feature]: Add VSR * [Feature]: Revert task to previous version
122 lines
3.9 KiB
Python
122 lines
3.9 KiB
Python
import random
|
|
import re
|
|
|
|
import torch
|
|
|
|
|
|
class MiniGPT4MMBenchPostProcessor:
|
|
""""Post processor for MiniGPT-4 on MMBench."""
|
|
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def __call__(self, output_token: torch.tensor, tokenizer) -> str:
|
|
|
|
if output_token[0] == 0:
|
|
output_token = output_token[1:]
|
|
if output_token[0] == 1:
|
|
output_token = output_token[1:]
|
|
output_text = tokenizer.decode(output_token,
|
|
add_special_tokens=False) # noqa
|
|
output_text = self._extract_key_words(output_text)
|
|
return output_text
|
|
|
|
def _extract_key_words(self, output_text: str) -> str:
|
|
|
|
output_text = output_text.split('###')[0]
|
|
output_text = output_text.split('Assistant:')[-1].strip()
|
|
output_text = output_text.strip('</s><s>')
|
|
output_text = output_text.strip('</Img>')
|
|
output_text = output_text.strip()
|
|
pattern = re.compile(r'([A-Z]\.)')
|
|
res = pattern.findall(output_text)
|
|
if len(res) > 0:
|
|
output_text = res[0][:-1]
|
|
return output_text
|
|
|
|
|
|
class MiniGPT4COCOCaptionPostProcessor:
|
|
""""Post processor for MiniGPT-4 on COCO Caption."""
|
|
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def __call__(self, output_token: torch.tensor, tokenizer) -> str:
|
|
|
|
if output_token[0] == 0:
|
|
output_token = output_token[1:]
|
|
if output_token[0] == 1:
|
|
output_token = output_token[1:]
|
|
output_text = tokenizer.decode(output_token,
|
|
add_special_tokens=False) # noqa
|
|
output_text = output_text.split('###')[0]
|
|
output_text = output_text.split('Assistant:')[-1].strip()
|
|
output_text = output_text.split('. ')[0]
|
|
output_text = output_text.strip('<Img>')
|
|
output_text = output_text.strip()
|
|
return output_text
|
|
|
|
|
|
class MiniGPT4ScienceQAPostProcessor:
|
|
""""Post processor for MiniGPT-4 on ScienceQA."""
|
|
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def __call__(self, output_token: torch.tensor, tokenizer) -> str:
|
|
|
|
if output_token[0] == 0:
|
|
output_token = output_token[1:]
|
|
if output_token[0] == 1:
|
|
output_token = output_token[1:]
|
|
output_text = tokenizer.decode(output_token,
|
|
add_special_tokens=False) # noqa
|
|
output_text = output_text.split('###')[0]
|
|
output_text = output_text.split('Assistant:')[-1].strip()
|
|
pattern = re.compile(r'\(([A-Z])\)')
|
|
output_text = pattern.findall(output_text)
|
|
if len(output_text) == 0:
|
|
output_text = random.choice(['A', 'B', 'C', 'D'])
|
|
else:
|
|
output_text = output_text[0]
|
|
return output_text
|
|
|
|
|
|
class MiniGPT4VQAPostProcessor:
|
|
""""Post processor for MiniGPT-4 on VQA."""
|
|
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def __call__(self, output_token: torch.tensor, tokenizer) -> str:
|
|
|
|
if output_token[0] == 0:
|
|
output_token = output_token[1:]
|
|
if output_token[0] == 1:
|
|
output_token = output_token[1:]
|
|
output_text = tokenizer.decode(output_token,
|
|
add_special_tokens=False) # noqa
|
|
output_text = output_text.split('###')[0]
|
|
output_text = output_text.split('Assistant:')[-1].strip()
|
|
return output_text
|
|
|
|
|
|
class MiniGPT4VSRPostProcessor:
|
|
""""Post processor for MiniGPT-4 on VSR."""
|
|
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def __call__(self, output_token: torch.tensor, tokenizer) -> str:
|
|
|
|
if output_token[0] == 0:
|
|
output_token = output_token[1:]
|
|
if output_token[0] == 1:
|
|
output_token = output_token[1:]
|
|
output_text = tokenizer.decode(output_token, add_special_tokens=False)
|
|
pattern = r'yes|no|Yes|No'
|
|
output_text = re.findall(pattern, output_text)
|
|
if len(output_text) > 0:
|
|
output_text = output_text[0].lower()
|
|
return output_text
|