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Bump torchvision from 0.10.0 to 0.13.0
Bumps torchvision from 0.10.0 to 0.13.0.
Release notes
Sourced from torchvision's releases.
TorchVision 0.13, including new Multi-weights API, new pre-trained weights, and more
Highlights
Models
Multi-weight support API
TorchVision v0.13 offers a new Multi-weight support API for loading different weights to the existing model builder methods:
from torchvision.models import *Old weights with accuracy 76.130%
resnet50(weights=ResNet50_Weights.IMAGENET1K_V1)
New weights with accuracy 80.858%
resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
Best available weights (currently alias for IMAGENET1K_V2)
Note that these weights may change across versions
resnet50(weights=ResNet50_Weights.DEFAULT)
Strings are also supported
resnet50(weights="IMAGENET1K_V2")
No weights - random initialization
resnet50(weights=None)
The new API bundles along with the weights important details such as the preprocessing transforms and meta-data such as labels. Here is how to make the most out of it:
from torchvision.io import read_image from torchvision.models import resnet50, ResNet50_Weightsimg = read_image("test/assets/encode_jpeg/grace_hopper_517x606.jpg")
Step 1: Initialize model with the best available weights
weights = ResNet50_Weights.DEFAULT model = resnet50(weights=weights) model.eval()
Step 2: Initialize the inference transforms
preprocess = weights.transforms()
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Commits
da3794eFix all broken URLs (#6176) (#6177)c7091ecAdding _log_api_usage_once to Swin's reusable components. (#6175)1a4afa9Fix push on release reference name (#6170) (#6171)61ecd18Make sure tests are executed on pull and on push to release but not tag (#6169)94c81c2M1 fixes cherry (#6167)9dd7cfdAdd new.. betastatus::directive and document Beta APIs (#6115) (#6165)3ced9c1Fix minor typo in optical flow gallery example (#6163) (#6164)31414e1Update _pil_constants.py (#6154) (#6156)685b689Fix ViT and Resnext docs (#6150) (#6151)072aa71Put back CelebA download (#6147) (#6149)- Additional commits viewable in compare view
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Superseded by #384.