* DetectMultiBackend() `--half` handling

* CI fixes

* rename .half to .fp16 to avoid conflict

* warmup fix

* val update

* engine update

* engine update

May resolve https://github.com/ultralytics/yolov5/issues/6947

May resolve https://github.com/ultralytics/yolov5/issues/6931

Resolves `AttributeError: 'Upsample' object has no attribute 'recompute_scale_factor'` first raised in https://github.com/ultralytics/yolov5/issues/5499

* Move `git_describe()` to general.py

* Move `git_describe()` to general.py

* Fix TRT `max_workspace_size` deprecation notice

* Update export.py

* Update export.py

Bumps [actions/checkout](https://github.com/actions/checkout) from 2 to 3.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v2...v3)

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updated-dependencies:
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Bumps [actions/setup-python](https://github.com/actions/setup-python) from 2 to 3.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v2...v3)

---
updated-dependencies:
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  dependency-type: direct:production
  update-type: version-update:semver-major
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* Assert engine precision #6777

* Default to FP32 inputs for TensorRT engines

* Default to FP16 TensorRT exports #6777

* Remove wrong line #6777

* Automatically adjust detect.py input precision #6777

* Automatically adjust val.py input precision #6777

* Add missing colon

* Cleanup

* Cleanup

* Remove default trt_fp16_input definition

* Experiment

* Reorder detect.py if statement to after half checks

* Update common.py

* Update export.py

* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update yolov5s.yaml

* Update yolov5s.yaml
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Cleanup

* Cleanup

* Update AutoAnchor

* Update AutoAnchor

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ciCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Update sweep.yaml

Changed focal loss gamma search range between 1 and 4

* Update sweep.yaml

lowered the min value to match default

* Update autoanchor.py

* Update autoanchor.py

* Update EMA

* Update EMA

* ratio invert

* fix ratio invert

* fix2 ratio invert

* warmup iterations to 100

* ema_k

* implement tau

* implement tau

Export failed for 1-channel input shape, 1-liner fix

* Update hyps

* Update hyp.VOC.yaml

* Update pathlib

* Update hyps

* Update hyps

* Update hyps

* Update hyps

* Switch default LR scheduler from cos to linear

Based on empirical results of training both ways on all YOLOv5 models.

* linear bug fix

* GH: add PR template

* Update CONTRIBUTING.md

* Update PULL_REQUEST_TEMPLATE.md

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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This is a torch bug, but they seem unable or unwilling to fix it so I'm creating a suppression in YOLOv5. 

Resolves https://github.com/ultralytics/yolov5/issues/6692

* Use `export_formats()` in export.py

* list fix

* refactor: use edgetpu flag

* fix: remove bitwise and assignation to tflite

* Cleanup and fix tflite

* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Integer division by a float yields a (rounded) float. This causes
the dataloader to crash when creating a range.

* Fix CoreML P6 inference

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Fix exporting saved_model: pb exceeds 2GB

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Replace TF v1.x API with TF v2.x API for saved_model export

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Clean up

* Remove lambda in tf.function()

* Revert "Remove lambda in tf.function()" to be compatible with TF v2.4

This reverts commit 46c7931f11dfdea6ae340c77287c35c30b9e0779.

* Fix for pre-commit.ci

* Cleanup1

* Cleanup2

* Backwards compatibility update

* Update common.py

* Update common.py

* Cleanup3
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Revert to 21.10 on autobuild fail