* Apple Metal Performance Shader (MPS) device support

Following https://pytorch.org/blog/introducing-accelerated-pytorch-training-on-mac/

Should work with Apple M1 devices with PyTorch nightly installed with command `--device mps`. Usage examples:
```bash
python train.py --device mps
python detect.py --device mps
python val.py --device mps
```

* Update device strategy to fix MPS issue

* Write .yaml file when exporting model to openvino

Write .yaml file automatically when exporting model to openvino to be used during inference

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* Update export.py

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Resolves https://github.com/ultralytics/yolov5/issues/7911#issuecomment-1133671255

* Removed shell=True from subprocess commands that require user inputs. Also removed unused arguments

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* Added check=True

* Revert line add

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

* Update Docker

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* Cleanup

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

* Autoinstall TensorRT if missing

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

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* add fp16 for coreml using --half

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* fix

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* Update export.py

Simplify code.

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* enable TensorFlow ops if flag --nms or --agnostic-nms is used

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* Update

* Update

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* SavedModel TF Serve Fix

Fix for https://github.com/ultralytics/yolov5/issues/7205 proposed by @tylertroy

* Update export.py

* precommit: yapf

* align isort

* fix

# Conflicts:
#	utils/plots.py

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* Update setup.cfg

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* Update wandb_utils.py

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* Update val.py

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* simplify colorstr

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* val run fix

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* PyTorch Hub tuple fix

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* PyTorch Hub tuple fix3

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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

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* Fix exporting saved_model: pb exceeds 2GB

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

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* Clean up

* Remove lambda in tf.function()

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

This reverts commit 46c7931f11.

* Fix for pre-commit.ci

* Cleanup1

* Cleanup2

* Backwards compatibility update

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* Cleanup3

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* Add benchmarks.py

* Update

* Add requirements

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* dataset autodownload from root

* Update

* Redirect to /dev/null

* sudo --help

* Cleanup

* Add exports pd df

* Updates

* Updates

* Updates

* Cleanup

* dir handling fix

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* Cleanup

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* Cleanup model_type

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* Fix zero-export handling with `if any(f):`

Partial fix for https://github.com/ultralytics/yolov5/issues/6563

* Cleanup

* Edge TPU compiler sudo fix

Allows for auto-install of Edge TPU compiler on non-sudo systems like the YOLOv5 Docker image.

@kalenmike

* Update export.py

* Update export.py

* Update export.py

* `export.py` automatic `forward_export`

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