model_inception_v3: Inception v3 model

In torchvision: Models, Datasets and Transformations for Images

Inception v3 model

Description

Architecture from Rethinking the Inception Architecture for Computer Vision The required minimum input size of the model is 75x75.

Usage

model_inception_v3(pretrained = FALSE, progress = TRUE, ...)

Arguments

pretrained	(bool): If TRUE, returns a model pre-trained on ImageNet
progress	(bool): If TRUE, displays a progress bar of the download to stderr
...	Used to pass keyword arguments to the Inception module: aux_logits (bool): If TRUE, add an auxiliary branch that can improve training. Default: TRUE transform_input (bool): If TRUE, preprocess the input according to the method with which it was trained on ImageNet. Default: FALSE

Note

Important: In contrast to the other models the inception_v3 expects tensors with a size of N x 3 x 299 x 299, so ensure your images are sized accordingly.

See Also

Other classification_model: model_alexnet(), model_convnext, model_efficientnet, model_efficientnet_v2, model_facenet, model_maxvit(), model_mobilenet_v2(), model_mobilenet_v3, model_resnet, model_vgg, model_vit

torchvision documentation built on Nov. 6, 2025, 9:07 a.m.