solving-occlusion
solving-occlusion copied to clipboard
Bump torchvision from 0.11.3 to 0.14.1
Bumps torchvision from 0.11.3 to 0.14.1.
Release notes
Sourced from torchvision's releases.
TorchVision 0.14.1 Release
This is a minor release, which is compatible with PyTorch 1.13.1. There are no new features added.
TorchVision 0.14, including new model registration API, new models, weights, augmentations, and more
Highlights
[BETA] New Model Registration API
Following up on the multi-weight support API that was released on the previous version, we have added a new model registration API to help users retrieve models and weights. There are now 4 new methods under the
torchvision.models
module:get_model
,get_model_weights
,get_weight
, andlist_models
. Here are examples of how we can use them:import torchvision from torchvision.models import get_model, get_model_weights, list_models
max_params = 5000000
tiny_models = [] for model_name in list_models(module=torchvision.models): weights_enum = get_model_weights(model_name) if len([w for w in weights_enum if w.meta["num_params"] <= max_params]) > 0: tiny_models.append(model_name)
print(tiny_models)
['mnasnet0_5', 'mnasnet0_75', 'mnasnet1_0', 'mobilenet_v2', ...]
model = get_model(tiny_models[0], weights="DEFAULT") print(sum(x.numel() for x in model.state_dict().values()))
2239188
As of now, this API is still beta and there might be changes in the future in order to improve its usability based on your feedback.
New Architecture and Model Variants
Classification Models
We’ve added the Swin Transformer V2 architecture along with pre-trained weights for its tiny/small/base variants. In addition, we have added support for the MaxViT transformer. Here is an example on how to use the models:
import torch from torchvision.models import *
image = torch.rand(1, 3, 224, 224) </tr></table>
... (truncated)
Commits
5e8e2f1
[Release only change] Advance version for minor release5ce4506
Increase inactivity timeout for binary build jobs (#6746) (#6747)f15f4e8
Set correct upload channel (#6744)531a2ea
Fix for windows and python 3.8 call to add_dll_directory (#6742) (#6743)95bef27
Fix windows python 3.8 required dlls not found (#6715) (#6716)5ff802b
Test against torch RC instead of nightly. Bump build version (#6717)3bd6ce9
[bugfix] Fix the output format for VideoClips.subset (#6700) (#6706)8762598
fix bug in output format for pyav (#6672) (#6703)dc6d86d
fix example galleries in documentation (#6701)673838f
Removing prototype related things from release/0.14 branch (#6687)- Additional commits viewable in compare view
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase
.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
-
@dependabot rebase
will rebase this PR -
@dependabot recreate
will recreate this PR, overwriting any edits that have been made to it -
@dependabot merge
will merge this PR after your CI passes on it -
@dependabot squash and merge
will squash and merge this PR after your CI passes on it -
@dependabot cancel merge
will cancel a previously requested merge and block automerging -
@dependabot reopen
will reopen this PR if it is closed -
@dependabot close
will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually -
@dependabot ignore this major version
will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) -
@dependabot ignore this minor version
will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) -
@dependabot ignore this dependency
will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)