examples/torch/common/models/classification/resnet_cifar10.py
def resnet34_cifar10(pretrained=False, progress=True, device="cpu", **kwargs):
    """Constructs a ResNet-34 model.
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
        progress (bool): If True, displays a progress bar of the download to stderr
    """
    return _resnet(
        "resnet34", BasicBlock, [3, 4, 6, 3], pretrained, progress, device, **kwargs
    )
Constructs a ResNet-34 model.
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
        progress (bool): If True, displays a progress bar of the download to stderr
    
Constructs a ResNet-34 model.
Constructs a ResNet - 34 model .
def resnet34_cifar10(pretrained=False, progress=True, device="cpu", **kwargs):
    return _resnet(
        "resnet34", BasicBlock, [3, 4, 6, 3], pretrained, progress, device, **kwargs
    )
def resnet34_cifar10 ( pretrained = False , progress = True , device = "cpu" , ** kwargs ) : return _resnet ( "resnet34" , BasicBlock , [ 3 , 4 , 6 , 3 ] , pretrained , progress , device , ** kwargs )
Constructs a ResNet-34 model.
Constructs a ResNet - 34 model .
"""Constructs a ResNet-34 model.
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
        progress (bool): If True, displays a progress bar of the download to stderr
    """
pretrained
If True, returns a model pre-trained on ImageNet
If True returns a model pre - trained on ImageNet
progress
If True, displays a progress bar of the download to stderr
If True displays a progress bar of the download to stderr
device