* New TensorFlow `TFCrossConv()` module

* Move from experimental to common

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* Add C3x

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* TFC3x bug fix

* TFC3x bug fix

* TFC3x bug fix

* Add TFDWConv g==c1==c2 check

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Bumps [cirrus-actions/rebase](https://github.com/cirrus-actions/rebase) from 1.6 to 1.7.
- [Release notes](https://github.com/cirrus-actions/rebase/releases)
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* New TensorFlow `TFDWConv()` module

Analog to DWConv() module:
8aa2085a7e/models/common.py (L53-L57)

* Fix and new activations() function

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Resolves bug report #7817

* Add `@threaded` decorator

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* add random_interpolation option to make model robust to interpolation methods

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* Fix precommit error

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@sergiossm

* Implement DDP `static_graph=True`

Experimental implementation of new PyTorch 1.11.0 DDP feature.

* Add 1.11.0 check

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* Pin downloads to release version

Fixes a release version to avoid forward-compatibility issues in future releases.

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* Ability to dowlnoad older assets

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* Cleanup

* Cleanup2

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* Update tutorial.ipynb

* Created using Colaboratory

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* FROM nvcr.io/nvidia/pytorch:22.04-py3

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Bumps [github/codeql-action](https://github.com/github/codeql-action) from 1 to 2.
- [Release notes](https://github.com/github/codeql-action/releases)
- [Changelog](https://github.com/github/codeql-action/blob/main/CHANGELOG.md)
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fix bug in issue #7650

Resolves https://github.com/ultralytics/yolov5/issues/7638

May help https://github.com/ultralytics/yolov5/issues/7631#issuecomment-1113007451

Improved robustness to filename edge cases like `data/images/zidane.23.jpg` that currently fail. May resolve https://github.com/ultralytics/yolov5/issues/7432

Solution proposed in https://github.com/ultralytics/yolov5/issues/7128 to TRT PyTorch Hub CUDA illegal memory errors.

* PyTorch Hub `_verbose=False` fix2

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* Update

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May partially resolve concerns in https://github.com/ultralytics/yolov5/pull/7537#discussion_r856843711

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* Add redundant weights download mirrors

This PR seeks to improve access worldwide to YOLOv5 weights. Universal access to AI for all is our core value, and we are against any censorship or restriction efforts.

I've uploaded the official YOLOv5 v6.1 weights to a primary backup bucket on GCP and to secondary backup on Google Drive at https://drive.google.com/drive/folders/1EFQTEUeXWSFww0luse2jB9M1QNZQGwNl. Autodownload with try the first two locations (GitHuB release assets and GCP bucket), and point users to the Google Drive folder if the first two fail.

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* support nomedia

* support nomedia for validation

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* Update train.py

* Revert no plot evolve

evolve plots do not contain any images

* Revert plot_results

contains no media

* Update wandb_utils.py

* sync-bn cleanup

* Cleanup

* Rename nomedia -> noplots

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* Update .pre-commit-config.yaml

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* Autoinstall TensorRT if missing

May resolve https://github.com/ultralytics/yolov5/issues/7464

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* Update export.py

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Verified fix for https://github.com/ultralytics/yolov5/pull/7525#issuecomment-1106081123