resnext50_32x4d#

holocron.models.resnext50_32x4d(pretrained: bool = False, checkpoint: Checkpoint | None = None, progress: bool = True, **kwargs: Any) → ResNet[source]#

ResNeXt-50 from “Aggregated Residual Transformations for Deep Neural Networks”

Parameters:

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

  • checkpoint – If specified, load that checkpoint on the model

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

  • kwargs – keyword args of _resnet

Returns:

classification model

Return type:

torch.nn.Module

class holocron.models.ResNeXt50_32x4d_Checkpoint(value)[source]#

The model builder above accepts the following values as the checkpoint parameter. ResNeXt50_32x4d_Checkpoint.DEFAULT is equivalent to ResNeXt50_32x4d_Checkpoint.IMAGENETTE

ResNeXt50_32x4d_Checkpoint.IMAGENETTE:

Also available as ResNeXt50_32x4d_Checkpoint.DEFAULT.

dataset

imagenette

top1-accuracy

0.9455

top5-accuracy

0.9949

url

link

sha256

5832c4ce33522a9e

size

88.1MB

num_params

23.0M

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