Migrations
/
pytorch-image-models
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Updating vit model defs for mult-weight support trial (vit first). Prepping for CLIP (laion2b and openai) fine-tuned weights.

Browse Source
pull/1520/head
Ross Wightman 2 years ago
parent 041709b470
commit 0761ce7a1b
3 changed files with 128 additions and 75 deletions
Show Stats Download Patch File Download Diff File

2
timm/models/helpers.py
Unescape View File

@ -158,7 +158,7 @@ def _resolve_pretrained_source(pretrained_cfg):
# hf-hub available as alternate weight source in default_cfg
load_from = 'hf-hub'
pretrained_loc = hf_hub_id
if load_from == 'hf-hub' and 'hf_hub_filename' in pretrained_cfg:
if load_from == 'hf-hub' and pretrained_cfg.get('hf_hub_filename', None):
# if a filename override is set, return tuple for location w/ (hub_id, filename)
pretrained_loc = pretrained_loc, pretrained_cfg['hf_hub_filename']
return load_from, pretrained_loc

177
timm/models/vision_transformer.py
Unescape View File

@ -53,81 +53,81 @@ def _cfg(url='', **kwargs):
default_cfgs = generate_defaults({
# patch models (weights from official Google JAX impl)
'vit_tiny_patch16_224.in21ft1k': _cfg(
'vit_tiny_patch16_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True),
'vit_tiny_patch16_384.in21ft1k': _cfg(
'vit_tiny_patch16_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_small_patch32_224.in21ft1k': _cfg(
'vit_small_patch32_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_32-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True),
'vit_small_patch32_384.in21ft1k': _cfg(
'vit_small_patch32_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_32-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_small_patch16_224.in21ft1k': _cfg(
'vit_small_patch16_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_16-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True),
'vit_small_patch16_384.in21ft1k': _cfg(
'vit_small_patch16_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_16-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_base_patch32_224.in21ft1k': _cfg(
'vit_base_patch32_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_32-i21k-300ep-lr_0.001-aug_medium1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True),
'vit_base_patch32_384.in21ft1k': _cfg(
'vit_base_patch32_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_32-i21k-300ep-lr_0.001-aug_light1-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_base_patch16_224.in21ft1k': _cfg(
'vit_base_patch16_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.01-res_224.npz',
custom_load=True),
'vit_base_patch16_384.in21ft1k': _cfg(
'vit_base_patch16_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.01-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_base_patch8_224.in21ft1k': _cfg(
'vit_base_patch8_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_8-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.01-res_224.npz',
custom_load=True),
'vit_large_patch32_384.in21ft1k': _cfg(
'vit_large_patch32_384.v1_in21k_ft_1k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_p32_384-9b920ba8.pth',
input_size=(3, 384, 384), crop_pct=1.0),
'vit_large_patch16_224.in21ft1k': _cfg(
'vit_large_patch16_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/L_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.1-sd_0.1--imagenet2012-steps_20k-lr_0.01-res_224.npz',
custom_load=True),
'vit_large_patch16_384.in21ft1k': _cfg(
'vit_large_patch16_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/L_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.1-sd_0.1--imagenet2012-steps_20k-lr_0.01-res_384.npz',
custom_load=True, input_size=(3, 384, 384), crop_pct=1.0),
'vit_large_patch14_224': _cfg(url=''),
'vit_huge_patch14_224': _cfg(url=''),
'vit_giant_patch14_224': _cfg(url=''),
'vit_gigantic_patch14_224': _cfg(url=''),
'vit_large_patch14_224.untrained': _cfg(url=''),
'vit_huge_patch14_224.untrained': _cfg(url=''),
'vit_giant_patch14_224.untrained': _cfg(url=''),
'vit_gigantic_patch14_224.untrained': _cfg(url=''),
# patch models, imagenet21k (weights from official Google JAX impl)
'vit_tiny_patch16_224.in21k': _cfg(
'vit_tiny_patch16_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_small_patch32_224.in21k': _cfg(
'vit_small_patch32_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_32-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_small_patch16_224.in21k': _cfg(
'vit_small_patch16_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/S_16-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_base_patch32_224.in21k': _cfg(
'vit_base_patch32_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_32-i21k-300ep-lr_0.001-aug_medium1-wd_0.03-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_base_patch16_224.in21k': _cfg(
'vit_base_patch16_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_base_patch8_224.in21k': _cfg(
'vit_base_patch8_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/B_8-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0.npz',
custom_load=True, num_classes=21843),
'vit_large_patch32_224.in21k': _cfg(
'vit_large_patch32_224.v1_in21k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_patch32_224_in21k-9046d2e7.pth',
num_classes=21843),
'vit_large_patch16_224.in21k': _cfg(
'vit_large_patch16_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/L_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.1-sd_0.1.npz',
custom_load=True, num_classes=21843),
'vit_huge_patch14_224.in21k': _cfg(
'vit_huge_patch14_224.v1_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/imagenet21k/ViT-H_14.npz',
hf_hub_id='timm/vit_huge_patch14_224_in21k',
custom_load=True, num_classes=21843),
@ -157,67 +157,111 @@ default_cfgs = generate_defaults({
'vit_base_patch16_224_miil.in21k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tresnet/vit_base_patch16_224_in21k_miil-887286df.pth',
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', num_classes=11221),
'vit_base_patch16_224_miil.in21ft1k': _cfg(
'vit_base_patch16_224_miil.in21k_ft_1k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tresnet/vit_base_patch16_224_1k_miil_84_4-2deb18e3.pth',
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear'),
# custom timm variants
'vit_base_patch16_rpn_224': _cfg(
'vit_base_patch16_rpn_224.in1k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/vit_base_patch16_rpn_224-sw-3b07e89d.pth'),
'vit_medium_patch16_gap_240.in12k': _cfg(
url='',
input_size=(3, 240, 240), crop_pct=0.95, num_classes=11821),
'vit_medium_patch16_gap_256.in12ft1k': _cfg(url='', input_size=(3, 256, 256), crop_pct=0.95),
'vit_medium_patch16_gap_384.in12ft1k': _cfg(url='', input_size=(3, 384, 384), crop_pct=0.95),
'vit_medium_patch16_gap_256.in12k_ft_1k': _cfg(
url='',
input_size=(3, 256, 256), crop_pct=0.95),
'vit_medium_patch16_gap_384.in12k_ft_1k': _cfg(
url='',
input_size=(3, 384, 384), crop_pct=0.95),
# CLIP pretrained image tower and related fine-tuned weights
'vit_base_patch32_224_clip.laion2b': _cfg(
'vit_base_patch32_clip_224.laion2b': _cfg(
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(
'vit_large_patch14_clip_224.laion2b': _cfg(
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(
'vit_huge_patch14_clip_224.laion2b': _cfg(
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(
'vit_giant_patch14_clip_224.laion2b': _cfg(
hf_hub_id='laion/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),
'vit_base_patch32_224_clip.laion2b_ft_in1k': _cfg(
'vit_base_patch32_clip_224.laion2b_ft_in1k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_large_patch14_224_clip.laion2b_ft_in1k': _cfg(
'vit_large_patch14_clip_224.laion2b_ft_in1k': _cfg(
hf_hub_id='',
mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD),
'vit_huge_patch14_224_clip.laion2b_ft_in1k': _cfg(
'vit_huge_patch14_clip_224.laion2b_ft_in1k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch32_224_clip.laion2b_ft_in12k_in1k': _cfg(
'vit_base_patch32_clip_224.laion2b_ft_in12k_in1k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_large_patch14_224_clip.laion2b_ft_in12k_in1k': _cfg(
'vit_large_patch14_clip_224.laion2b_ft_in12k_in1k': _cfg(
hf_hub_id='',
mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD),
'vit_huge_patch14_224_clip.laion2b_ft_in12k_in1k': _cfg(
'vit_huge_patch14_clip_224.laion2b_ft_in12k_in1k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch32_224_clip.laion2b_ft_in12k': _cfg(
'vit_base_patch32_clip_224.laion2b_ft_in12k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=11821),
'vit_large_patch14_224_clip.laion2b_ft_in12k': _cfg(
'vit_large_patch14_clip_224.laion2b_ft_in12k': _cfg(
hf_hub_id='',
mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, num_classes=11821),
'vit_huge_patch14_224_clip.laion2b_ft_in12k': _cfg(
'vit_huge_patch14_clip_224.laion2b_ft_in12k': _cfg(
hf_hub_id='',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=11821),
'vit_base_patch32_clip_224.openai': _cfg(
hf_hub_id='timm/clip_vit_base_patch32_224.openai',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_base_patch16_clip_224.openai': _cfg(
hf_hub_id='timm/clip_vit_base_patch16_224.openai',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_large_patch14_clip_224.openai': _cfg(
hf_hub_id='timm/clip_vit_large_patch14_224.openai',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=768),
'vit_base_patch32_clip_224.openai_ft_in1k': _cfg(
hf_hub_id='timm/vit_base_patch32_clip_224.openai_ft_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch16_clip_224.openai_ft_in1k': _cfg(
hf_hub_id='timm/vit_base_patch16_clip_224.openai_ft_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_large_patch14_clip_224.openai_ft_in1k': _cfg(
hf_hub_id='timm/vit_large_patch14_clip_224.openai_ft_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch32_clip_224.openai_ft_in12k_in1k': _cfg(
hf_hub_id='timm/vit_base_patch32_clip_224.openai_ft_in12k_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch16_clip_224.openai_ft_in12k_in1k': _cfg(
hf_hub_id='timm/vit_base_patch16_clip_224.openai_ft_in12k_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_large_patch14_clip_224.openai_ft_in12k_in1k': _cfg(
hf_hub_id='timm/vit_large_patch14_clip_224.openai_ft_in12k_in1k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD),
'vit_base_patch32_clip_224.openai_ft_in12k': _cfg(
hf_hub_id='timm/vit_base_patch32_clip_224.openai_ft_in12k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=11821),
'vit_base_patch16_clip_224.openai_ft_in12k': _cfg(
hf_hub_id='timm/vit_base_patch16_clip_224.openai_ft_in12k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=11821),
'vit_large_patch14_clip_224.openai_ft_in12k': _cfg(
hf_hub_id='timm/vit_large_patch14_clip_224.openai_ft_in12k',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=11821),
# experimental (may be removed)
'vit_base_patch32_plus_256': _cfg(url='', input_size=(3, 256, 256), crop_pct=0.95),
'vit_base_patch16_plus_240': _cfg(url='', input_size=(3, 240, 240), crop_pct=0.95),
@ -1015,17 +1059,6 @@ def vit_base_patch16_224_miil(pretrained=False, **kwargs):
return model
@register_model
def vit_base_patch32_224_clip(pretrained=False, **kwargs):
""" ViT-B/32
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=32, embed_dim=768, depth=12, num_heads=12, pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_base_patch32_224_clip', pretrained=pretrained, **model_kwargs)
return model
@register_model
def vit_medium_patch16_gap_240(pretrained=False, **kwargs):
""" ViT-Base (ViT-M/16) w/o class token, w/ avg-pool @ 240x240
@ -1060,36 +1093,58 @@ def vit_medium_patch16_gap_384(pretrained=False, **kwargs):
@register_model
def vit_large_patch14_224_clip(pretrained=False, **kwargs):
def vit_base_patch32_clip_224(pretrained=False, **kwargs):
""" ViT-B/32
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=32, embed_dim=768, depth=12, num_heads=12, pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_base_patch32_clip_224', pretrained=pretrained, **model_kwargs)
return model
@register_model
def vit_base_patch16_clip_224(pretrained=False, **kwargs):
""" ViT-B/16
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=16, embed_dim=768, depth=12, num_heads=12, pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_base_patch16_clip_224', pretrained=pretrained, **model_kwargs)
return model
@register_model
def vit_large_patch14_clip_224(pretrained=False, **kwargs):
""" ViT-Large model (ViT-L/14)
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=14, embed_dim=1024, depth=24, num_heads=16, pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_large_patch14_224_clip', pretrained=pretrained, **model_kwargs)
model = _create_vision_transformer('vit_large_patch14_clip_224', pretrained=pretrained, **model_kwargs)
return model
@register_model
def vit_huge_patch14_224_clip(pretrained=False, **kwargs):
def vit_huge_patch14_clip_224(pretrained=False, **kwargs):
""" ViT-Huge model (ViT-H/14) from original paper (https://arxiv.org/abs/2010.11929).
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=14, embed_dim=1280, depth=32, num_heads=16, pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_huge_patch14_224_clip', pretrained=pretrained, **model_kwargs)
model = _create_vision_transformer('vit_huge_patch14_clip_224', pretrained=pretrained, **model_kwargs)
return model
@register_model
def vit_giant_patch14_224_clip(pretrained=False, **kwargs):
def vit_giant_patch14_clip_224(pretrained=False, **kwargs):
""" ViT-Giant (little-g) model (ViT-g/14) from `Scaling Vision Transformers` - https://arxiv.org/abs/2106.04560
Pretrained weights from CLIP image tower trained on LAION-2B image-text pairs.
"""
model_kwargs = dict(
patch_size=14, embed_dim=1408, mlp_ratio=48/11, depth=40, num_heads=16,
pre_norm=True, norm_layer=nn.LayerNorm, **kwargs)
model = _create_vision_transformer('vit_giant_patch14_224_clip', pretrained=pretrained, **model_kwargs)
model = _create_vision_transformer('vit_giant_patch14_clip_224', pretrained=pretrained, **model_kwargs)
return model

24
timm/models/vision_transformer_hybrid.py
Unescape View File

@ -41,45 +41,43 @@ def _cfg(url='', **kwargs):
default_cfgs = generate_defaults({
# hybrid in-1k models (weights from official JAX impl where they exist)
'vit_tiny_r_s16_p8_224.in21ft1k': _cfg(
'vit_tiny_r_s16_p8_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R_Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True,
first_conv='patch_embed.backbone.conv'),
'vit_tiny_r_s16_p8_384.in21ft1k': _cfg(
'vit_tiny_r_s16_p8_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R_Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
first_conv='patch_embed.backbone.conv', input_size=(3, 384, 384), crop_pct=1.0, custom_load=True),
'vit_small_r26_s32_224.in21ft1k': _cfg(
'vit_small_r26_s32_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R26_S_32-i21k-300ep-lr_0.001-aug_light0-wd_0.03-do_0.1-sd_0.1--imagenet2012-steps_20k-lr_0.03-res_224.npz',
custom_load=True,
),
'vit_small_r26_s32_384.in21ft1k': _cfg(
'vit_small_r26_s32_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R26_S_32-i21k-300ep-lr_0.001-aug_medium2-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.npz',
input_size=(3, 384, 384), crop_pct=1.0, custom_load=True),
'vit_base_r26_s32_224': _cfg(),
'vit_base_r50_s16_224': _cfg(),
'vit_base_r50_s16_384.in1k': _cfg(
'vit_base_r50_s16_384.v1_in21k_ft_1k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_resnet50_384-9fd3c705.pth',
input_size=(3, 384, 384), crop_pct=1.0),
'vit_large_r50_s32_224.in21ft1k': _cfg(
'vit_large_r50_s32_224.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R50_L_32-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.1-sd_0.1--imagenet2012-steps_20k-lr_0.01-res_224.npz',
custom_load=True,
),
'vit_large_r50_s32_384.in21ft1k': _cfg(
'vit_large_r50_s32_384.augreg_in21k_ft_1k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R50_L_32-i21k-300ep-lr_0.001-aug_medium2-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.01-res_384.npz',
input_size=(3, 384, 384), crop_pct=1.0, custom_load=True,
),
# hybrid in-21k models (weights from official Google JAX impl where they exist)
'vit_tiny_r_s16_p8_224.in21k': _cfg(
'vit_tiny_r_s16_p8_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R_Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0.npz',
num_classes=21843, crop_pct=0.9, first_conv='patch_embed.backbone.conv', custom_load=True),
'vit_small_r26_s32_224.in21k': _cfg(
'vit_small_r26_s32_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R26_S_32-i21k-300ep-lr_0.001-aug_medium2-wd_0.03-do_0.0-sd_0.0.npz',
num_classes=21843, crop_pct=0.9, custom_load=True),
'vit_base_r50_s16_224.in21k': _cfg(
'vit_base_r50_s16_224.v1_in21k': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_resnet50_224_in21k-6f7c7740.pth',
num_classes=21843, crop_pct=0.9),
'vit_large_r50_s32_224.in21k': _cfg(
'vit_large_r50_s32_224.augreg_in21k': _cfg(
url='https://storage.googleapis.com/vit_models/augreg/R50_L_32-i21k-300ep-lr_0.001-aug_medium2-wd_0.1-do_0.0-sd_0.0.npz',
num_classes=21843, crop_pct=0.9, custom_load=True),

Write Preview
Loading…
Cancel
Save