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hubconf.py
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hubconf.py
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from models.resnet import resnet18 as _resnet18
from models.resnet import resnet50 as _resnet50
from models.mobilenetv2 import mobilenetv2 as _mobilenetv2
from models.mnasnet import mnasnet as _mnasnet
from models.regnet import regnetx_600m as _regnetx_600m
from models.regnet import regnetx_3200m as _regnetx_3200m
from torch.hub import load_state_dict_from_url
dependencies = ['torch']
def resnet18(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _resnet18(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/resnet18_imagenet.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint)
return model
def resnet50(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _resnet50(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/resnet50_imagenet.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint)
return model
def mobilenetv2(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _mobilenetv2(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/mobilenetv2.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint['model'])
return model
def regnetx_600m(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _regnetx_600m(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/regnet_600m.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint)
return model
def regnetx_3200m(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _regnetx_3200m(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/regnet_3200m.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint)
return model
def mnasnet(pretrained=False, **kwargs):
# Call the model, load pretrained weights
model = _mnasnet(**kwargs)
if pretrained:
load_url = 'https://github.com/yhhhli/BRECQ/releases/download/v1.0/mnasnet.pth.tar'
checkpoint = load_state_dict_from_url(url=load_url, map_location='cpu', progress=True)
model.load_state_dict(checkpoint)
return model