|
from timm.models import ByoModelCfg, ByoBlockCfg, ByobNet |
|
|
|
from ._base import EncoderMixin |
|
import torch.nn as nn |
|
|
|
|
|
class GERNetEncoder(ByobNet, EncoderMixin): |
|
def __init__(self, out_channels, depth=5, **kwargs): |
|
super().__init__(**kwargs) |
|
self._depth = depth |
|
self._out_channels = out_channels |
|
self._in_channels = 3 |
|
|
|
del self.head |
|
|
|
def get_stages(self): |
|
return [ |
|
nn.Identity(), |
|
self.stem, |
|
self.stages[0], |
|
self.stages[1], |
|
self.stages[2], |
|
nn.Sequential(self.stages[3], self.stages[4], self.final_conv) |
|
] |
|
|
|
def forward(self, x): |
|
stages = self.get_stages() |
|
|
|
features = [] |
|
for i in range(self._depth + 1): |
|
x = stages[i](x) |
|
features.append(x) |
|
|
|
return features |
|
|
|
def load_state_dict(self, state_dict, **kwargs): |
|
state_dict.pop("head.fc.weight", None) |
|
state_dict.pop("head.fc.bias", None) |
|
super().load_state_dict(state_dict, **kwargs) |
|
|
|
|
|
regnet_weights = { |
|
'timm-gernet_s': { |
|
'imagenet': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-ger-weights/gernet_s-756b4751.pth', |
|
}, |
|
'timm-gernet_m': { |
|
'imagenet': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-ger-weights/gernet_m-0873c53a.pth', |
|
}, |
|
'timm-gernet_l': { |
|
'imagenet': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-ger-weights/gernet_l-f31e2e8d.pth', |
|
}, |
|
} |
|
|
|
pretrained_settings = {} |
|
for model_name, sources in regnet_weights.items(): |
|
pretrained_settings[model_name] = {} |
|
for source_name, source_url in sources.items(): |
|
pretrained_settings[model_name][source_name] = { |
|
"url": source_url, |
|
'input_range': [0, 1], |
|
'mean': [0.485, 0.456, 0.406], |
|
'std': [0.229, 0.224, 0.225], |
|
'num_classes': 1000 |
|
} |
|
|
|
timm_gernet_encoders = { |
|
'timm-gernet_s': { |
|
'encoder': GERNetEncoder, |
|
"pretrained_settings": pretrained_settings["timm-gernet_s"], |
|
'params': { |
|
'out_channels': (3, 13, 48, 48, 384, 1920), |
|
'cfg': ByoModelCfg( |
|
blocks=( |
|
ByoBlockCfg(type='basic', d=1, c=48, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='basic', d=3, c=48, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='bottle', d=7, c=384, s=2, gs=0, br=1 / 4), |
|
ByoBlockCfg(type='bottle', d=2, c=560, s=2, gs=1, br=3.), |
|
ByoBlockCfg(type='bottle', d=1, c=256, s=1, gs=1, br=3.), |
|
), |
|
stem_chs=13, |
|
stem_pool=None, |
|
num_features=1920, |
|
) |
|
}, |
|
}, |
|
'timm-gernet_m': { |
|
'encoder': GERNetEncoder, |
|
"pretrained_settings": pretrained_settings["timm-gernet_m"], |
|
'params': { |
|
'out_channels': (3, 32, 128, 192, 640, 2560), |
|
'cfg': ByoModelCfg( |
|
blocks=( |
|
ByoBlockCfg(type='basic', d=1, c=128, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='basic', d=2, c=192, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='bottle', d=6, c=640, s=2, gs=0, br=1 / 4), |
|
ByoBlockCfg(type='bottle', d=4, c=640, s=2, gs=1, br=3.), |
|
ByoBlockCfg(type='bottle', d=1, c=640, s=1, gs=1, br=3.), |
|
), |
|
stem_chs=32, |
|
stem_pool=None, |
|
num_features=2560, |
|
) |
|
}, |
|
}, |
|
'timm-gernet_l': { |
|
'encoder': GERNetEncoder, |
|
"pretrained_settings": pretrained_settings["timm-gernet_l"], |
|
'params': { |
|
'out_channels': (3, 32, 128, 192, 640, 2560), |
|
'cfg': ByoModelCfg( |
|
blocks=( |
|
ByoBlockCfg(type='basic', d=1, c=128, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='basic', d=2, c=192, s=2, gs=0, br=1.), |
|
ByoBlockCfg(type='bottle', d=6, c=640, s=2, gs=0, br=1 / 4), |
|
ByoBlockCfg(type='bottle', d=5, c=640, s=2, gs=1, br=3.), |
|
ByoBlockCfg(type='bottle', d=4, c=640, s=1, gs=1, br=3.), |
|
), |
|
stem_chs=32, |
|
stem_pool=None, |
|
num_features=2560, |
|
) |
|
}, |
|
}, |
|
} |
|
|