composer.models.resnet.model#
A ComposerClassifier
wrapper around the torchvision implementations of the ResNet model family.
Classes
A |
- class composer.models.resnet.model.ComposerResNet(model_name, num_classes=1000, pretrained=False, groups=1, width_per_group=64, initializers=None)[source]#
Bases:
composer.models.tasks.classification.ComposerClassifier
A
ComposerClassifier
wrapper around the torchvision implementations of the ResNet model family.From Deep Residual Learning for Image Recognition (He et al, 2015).
- Parameters
model_name (str) โ Name of the ResNet model instance. Either [
"resnet18"
,"resnet34"
,"resnet50"
,"resnet101"
,"resnet152"
].num_classes (int, optional) โ The number of classes. Needed for classification tasks. Default:
1000
.pretrained (bool, optional) โ If True, use ImageNet pretrained weights. Default:
False
.groups (int, optional) โ Number of filter groups for the 3x3 convolution layer in bottleneck blocks. Default:
1
.width_per_group (int, optional) โ Initial width for each convolution group. Width doubles after each stage. Default:
64
.initializers (List[Initializer], optional) โ Initializers for the model.
None
for no initialization. Default:None
.
Example:
from composer.models import ComposerResNet model = ComposerResNet(model_name='resnet18') # creates a torchvision resnet18 for image classification