sknet50#

holocron.models.sknet50(pretrained: bool = False, checkpoint: Checkpoint | None = None, progress: bool = True, **kwargs: Any) → ResNet[source]#

SKNet-50 from “Selective Kernel Networks”

Parameters:

  • pretrained (bool) – If True, returns a model pre-trained on ImageNet

  • checkpoint – If specified, the model’s parameters will be set to the checkpoint’s values

  • progress (bool) – If True, displays a progress bar of the download to stderr

  • kwargs – keyword args of _sknet

Returns:

classification model

Return type:

torch.nn.Module

class holocron.models.SKNet50_Checkpoint(value)[source]#

The model builder above accepts the following values as the checkpoint parameter. SKNet50_Checkpoint.DEFAULT is equivalent to SKNet50_Checkpoint.IMAGENETTE

SKNet50_Checkpoint.IMAGENETTE:

Also available as SKNet50_Checkpoint.DEFAULT.

dataset

imagenette

top1-accuracy

0.9437

top5-accuracy

0.9954

url

link

sha256

e2349031c838a466

size

134.7MB

num_params

35.2M

categories

tench, English springer, cassette player, … (7 omitted)

input_shape

(3, 224, 224)

mean

(0.485, 0.456, 0.406)

std

(0.229, 0.224, 0.225)

interpolation

InterpolationMode.BILINEAR

commit

6e32c5b