Display device_name="MYRIAD" for Intel NCS2 option per user question in https://github.com/ultralytics/yolov5/issues/8154

Improve DDP console response in https://github.com/ultralytics/yolov5/issues/8283

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Avoid potential issues with deterministic ops. 

[ ] - verify for identical mAP to master

* HUB dataset_stats() error reporting

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* Update dataloaders.py
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* Prefer MPS over CPU if available

* Update torch_utils.py

Negatively impacts YouTube inference but removes any lag on webcams/RTSP/RTMP etc.

Resolves https://github.com/ultralytics/yolov5/issues/4465

* Reject webcam inference on Colab/Kaggle

Improve user error understanding for https://github.com/ultralytics/yolov5/issues/8180

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* cleanup
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Bumps [actions/setup-python](https://github.com/actions/setup-python) from 3 to 4.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v3...v4)

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  dependency-type: direct:production
  update-type: version-update:semver-major
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* Update dataloaders.py

* Update dataloaders.py

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* Update

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* Update

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* Update

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* Update

* Update

* AutoBatch checks against failed solutions

@kalenmike this is a simple improvement to AutoBatch to verify that returned solutions have not already failed, i.e. return batch-size 8 when 8 already produced CUDA out of memory.

This is a halfway fix until I can implement a 'final solution' that will actively verify the solved-for batch size rather than passively assume it works.

* Update autobatch.py

* Update autobatch.py

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updates:
- [github.com/asottile/pyupgrade: v2.32.0 → v2.32.1](https://github.com/asottile/pyupgrade/compare/v2.32.0...v2.32.1)
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* experimental.py Apple MPS fix

May resolve https://github.com/ultralytics/yolov5/issues/8102

* Update experimental.py

* Update experimental.py

* Improved dataset error introspection

Intended to help https://github.com/ultralytics/yolov5/issues/8090

* Update general.py

* Update ci-testing.yml

* Update ci-testing.yml

* Update ci-testing.yml

* Update docker.yml

Fixed FP32 TRT  model export
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make init bias better, 
I think `detach` is more safer than `data`

Simplify and update `--save-period` epoch 0

* Pin `protobuf==3.20.1`

* Update requirements.txt

* Update ci-testing.yml

Pin protobuf==3.20.1

Resolve protobuf 4 issues.

Avoids openvino-dev conflicts

* Add warning emoji on `--conf > 0.001`

* Update val.py

* Update and rename ci-testing.yml to ci.yml

* Update ci.yml

* Update ci.yml

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Attempt to resolve Windows issues

* Add `psutil` and `ipython` to requirements.txt

Lightweight packages used by YOLOv5 for system utilization (psutil) and interactive notebooks (IPython)

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* sort alphabetically
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* Remove `formats` variable to avoid `pd` conflict

* Update export.py

Update requirements.txt

* Reduce AMP check to detections verification

More robust and faster

* Update general.py

* Update general.py