mirror of
https://github.com/open-compass/opencompass.git
synced 2025-05-30 16:03:24 +08:00

* [Feature]: Add Openflamingo MMBench * [Fix]: Fix import error * [Fix]: Revert task config * [Fix]: Fix path bug
74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
# dataloader settings
|
|
val_pipeline = [
|
|
dict(type='mmpretrain.PILToNumpy'),
|
|
dict(type='mmpretrain.ResizeEdge',
|
|
scale=224,
|
|
interpolation='bicubic',
|
|
backend='pillow'),
|
|
dict(type='CenterCrop', crop_size=(224, 224)),
|
|
dict(type='mmpretrain.PackInputs',
|
|
algorithm_keys=[
|
|
'question', 'options', 'category', 'l2-category', 'index',
|
|
'context', 'options_dict'
|
|
])
|
|
]
|
|
|
|
dataset = dict(type='opencompass.MMBenchDataset',
|
|
data_file='data/mmbench/mmbench_test_20230712.tsv',
|
|
pipeline=val_pipeline)
|
|
|
|
openflamingo_dataloader = dict(
|
|
batch_size=1,
|
|
num_workers=4,
|
|
dataset=dataset,
|
|
sampler=dict(type='DefaultSampler', shuffle=False),
|
|
collate_fn=dict(type='default_collate'),
|
|
persistent_workers=True,
|
|
)
|
|
|
|
# model settings
|
|
openflamingo_model = dict(
|
|
type='openflamingo',
|
|
data_preprocessor=dict(
|
|
type='mmpretrain.MultiModalDataPreprocessor',
|
|
mean=[122.770938, 116.7460125, 104.09373615],
|
|
std=[68.5005327, 66.6321579, 70.32316305],
|
|
to_rgb=True,
|
|
),
|
|
tokenizer=dict(type='mmpretrain.LlamaTokenizer',
|
|
name_or_path='decapoda-research/llama-7b-hf'),
|
|
vision_encoder=dict(
|
|
type='mmpretrain.VisionTransformer',
|
|
arch='l',
|
|
patch_size=14,
|
|
pre_norm=True,
|
|
norm_cfg=dict(type='LN', eps=1e-5),
|
|
layer_cfgs=dict(act_cfg=dict(type='mmpretrain.QuickGELU')),
|
|
final_norm=False,
|
|
out_type='raw',
|
|
pretrained= # noqa: E251
|
|
'/path/to/vision/encoder', # noqa
|
|
),
|
|
lang_encoder=dict(
|
|
base=dict(type='mmpretrain.AutoModelForCausalLM',
|
|
name_or_path=
|
|
'decapoda-research/llama-7b-hf',
|
|
local_files_only=True),
|
|
adapter=dict(type='mmpretrain.FlamingoLMAdapter',
|
|
vis_hidden_size=1024,
|
|
cross_attn_every_n_layers=4,
|
|
use_media_placement_augmentation=False),
|
|
),
|
|
generation_cfg=dict(num_beams=3, max_new_tokens=20, length_penalty=-2.0),
|
|
)
|
|
|
|
# evaluation settings
|
|
openflamingo_evaluator = [
|
|
dict(
|
|
type='opencompass.DumpResults',
|
|
save_path= # noqa: E251
|
|
'work_dirs/9b-flamingo/9b-flamingo-mmbench.xlsx')
|
|
]
|
|
|
|
openflamingo_load_from = '/path/to/pretrained/weights' # noqa
|