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Add hf hub entries for laion2b clip models, add huggingface_hub dependency, update some setup/reqs, torch >= 1.7

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pull/1467/head
Ross Wightman 2 years ago
parent 9d65557be3
commit e069249a2d
5 changed files with 30 additions and 20 deletions
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5
requirements.txt
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@ -1,3 +1,4 @@
torch>=1.4.0
torchvision>=0.5.0
torch>=1.7
torchvision
pyyaml
huggingface_hub

9
setup.py
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@ -25,13 +25,15 @@ setup(
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 3 - Alpha',
'Development Status :: 4 - Beta',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: Apache Software License',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Software Development',
@ -40,9 +42,10 @@ setup(
],
# Note that this is a string of words separated by whitespace, not a list.
keywords='pytorch pretrained models efficientnet mobilenetv3 mnasnet',
keywords='pytorch pretrained models efficientnet mobilenetv3 mnasnet resnet vision transformer vit',
packages=find_packages(exclude=['convert', 'tests', 'results']),
include_package_data=True,
install_requires=['torch >= 1.4', 'torchvision'],
install_requires=['torch >= 1.7', 'torchvision', 'pyyaml', 'huggingface_hub'],
python_requires='>=3.6',
)

2
tests/test_models.py
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@ -38,7 +38,7 @@ if 'GITHUB_ACTIONS' in os.environ:
EXCLUDE_FILTERS = [
'*efficientnet_l2*', '*resnext101_32x48d', '*in21k', '*152x4_bitm', '*101x3_bitm', '*50x3_bitm',
'*nfnet_f3*', '*nfnet_f4*', '*nfnet_f5*', '*nfnet_f6*', '*nfnet_f7*', '*efficientnetv2_xl*',
'*resnetrs350*', '*resnetrs420*', 'xcit_large_24_p8*', 'vit_huge*', 'vit_g*', 'swin*huge*',
'*resnetrs350*', '*resnetrs420*', 'xcit_large_24_p8*', 'vit_huge*', 'vit_gi*', 'swin*huge*',
'swin*giant*']
NON_STD_EXCLUDE_FILTERS = ['vit_huge*', 'vit_gi*', 'swin*giant*']
else:

2
timm/data/constants.py
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@ -5,3 +5,5 @@ IMAGENET_INCEPTION_MEAN = (0.5, 0.5, 0.5)
IMAGENET_INCEPTION_STD = (0.5, 0.5, 0.5)
IMAGENET_DPN_MEAN = (124 / 255, 117 / 255, 104 / 255)
IMAGENET_DPN_STD = tuple([1 / (.0167 * 255)] * 3)
OPENAI_CLIP_MEAN = (0.48145466, 0.4578275, 0.40821073)
OPENAI_CLIP_STD = (0.26862954, 0.26130258, 0.27577711)

32
timm/models/vision_transformer.py
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@ -30,7 +30,8 @@ import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD,\
OPENAI_CLIP_MEAN, OPENAI_CLIP_STD
from .helpers import build_model_with_cfg, resolve_pretrained_cfg, named_apply, adapt_input_conv, checkpoint_seq
from .layers import PatchEmbed, Mlp, DropPath, trunc_normal_, lecun_normal_
from .registry import register_model
@ -106,7 +107,7 @@ default_cfgs = {
'vit_large_patch14_224': _cfg(url=''),
'vit_huge_patch14_224': _cfg(url=''),
'vit_giant_patch14_224': _cfg(url=''),
'vit_gee_patch14_224': _cfg(url=''),
'vit_gigantic_patch14_224': _cfg(url=''),
# patch models, imagenet21k (weights from official Google JAX impl)
@ -179,17 +180,21 @@ default_cfgs = {
'vit_base_patch16_18x2_224': _cfg(url=''),
'vit_base_patch32_224_clip_laion2b': _cfg(
hf_hub_id='',
num_classes=512),
hf_hub_id='laion/CLIP-ViT-B-32-laion2B-s34B-b79K',
hf_hub_filename='open_clip_pytorch_model.bin',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_large_patch14_224_clip_laion2b': _cfg(
hf_hub_id='',
num_classes=768),
hf_hub_id='laion/CLIP-ViT-L-14-laion2B-s32B-b82K',
hf_hub_filename='open_clip_pytorch_model.bin',
mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, num_classes=768),
'vit_huge_patch14_224_clip_laion2b': _cfg(
hf_hub_id='',
num_classes=1024),
hf_hub_id='laion/CLIP-ViT-H-14-laion2B-s32B-b79K',
hf_hub_filename='open_clip_pytorch_model.bin',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=1024),
'vit_giant_patch14_224_clip_laion2b': _cfg(
hf_hub_id='',
num_classes=1024),
hf_hub_id='CLIP-ViT-g-14-laion2B-s12B-b42K',
hf_hub_filename='open_clip_pytorch_model.bin',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=1024),
}
@ -960,12 +965,11 @@ def vit_giant_patch14_224(pretrained=False, **kwargs):
@register_model
def vit_gee_patch14_224(pretrained=False, **kwargs):
""" ViT-GEE (big-G) model (ViT-G/14) from `Scaling Vision Transformers` - https://arxiv.org/abs/2106.04560
As per https://twitter.com/wightmanr/status/1570549064667889666
def vit_gigantic_patch14_224(pretrained=False, **kwargs):
""" ViT-Gigantic (big-G) model (ViT-G/14) from `Scaling Vision Transformers` - https://arxiv.org/abs/2106.04560
"""
model_kwargs = dict(patch_size=14, embed_dim=1664, mlp_ratio=64/13, depth=48, num_heads=16, **kwargs)
model = _create_vision_transformer('vit_gee_patch14_224', pretrained=pretrained, **model_kwargs)
model = _create_vision_transformer('vit_gigantic_patch14_224', pretrained=pretrained, **model_kwargs)
return model

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