* Update train.py explicit arguments

* Update train.py

* Add run method

* Eliminate `total_batch_size` variable

* cleanup

* Update train.py

* Update DDP for `torch.distributed.run`

* Add LOCAL_RANK

* remove opt.local_rank

* backend="gloo|nccl"

* print

* print

* debug

* debug

* os.getenv

* gloo

* gloo

* gloo

* cleanup

* fix getenv

* cleanup

* cleanup destroy

* try nccl

* return opt

* add --local_rank

* add timeout

* add init_method

* gloo

* move destroy

* move destroy

* move print(opt) under if RANK

* destroy only RANK 0

* move destroy inside train()

* restore destroy outside train()

* update print(opt)

* cleanup

* nccl

* gloo with 60 second timeout

* update namespace printing

* Slightly modify CLI execution

This simple change makes it easier to run the primary functions of this
repo (train/detect/test) from within Python. An object which represents
`opt` can be constructed and fed to the `main` function of each of these
modules, rather than having to call the lower level functions directly,
or run the module as a script.

* Update export.py

Add CLI parsing update for more convenient module usage within Python.
Co-authored-by: Lewis Belcher <lb@desupervised.io>

* Create shortcircuit in augment_hsv when hyperparameter are zero

* implement faster opt-in
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Swapped order of operations for faster first per https://github.com/ultralytics/yolov5/commit/f527704cd32c42bc0bba9cce04601783b8563204#r52362419

* EMA changes for pre-model's batch_size

* Update train.py

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

* Cache v0.3: improved corrupt image/label reporting

Fix for https://github.com/ultralytics/yolov5/issues/3656#issuecomment-863660899

* cleanup

* Remove `/weights` directory

* cleanup

* Update `dataset_stats()` to list of dicts

@KalenMike

* Update datasets.py

Be more user-friendly to new users

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

* premature end of JPEG images

* PEP8 reformat
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update `check_file()`

* Update datasets.py

* supress wandb images size mismatch warning

* supress wandb images size mismatch warning

* PEP8 reformat and optimize imports
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* 'changes-in_dataset'

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

* Update README.md

* added hosted images

* added new logo

* testing image hosting

* changed svgs to pngs

* removed old header

* Update README.md

* correct colab image source

* splash.jpg

* rocket and W&B fix

* added contributing template

* added social media to top section

* increased size of top social media

* cleanup and updates

* rearrange quickstarts

* API cleanup

* PyTorch Hub cleanup

* Add tutorials

* cleanup

* update CONTRIBUTING.md

* Update README.md

* update wandb link

* Update README.md

* remove tutorials header

* update environments and integrations

* Comment API image

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* double spaces after section

* Update README.md

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

@KalenMike this is a PR to add image filenames and labels to our stats dictionary and to save the dictionary to JSON. Save location is next to the train labels.cache file. The single JSON contains all stats for entire dataset.

Usage example:
```python
from utils.datasets import *

dataset_stats('coco128.yaml', verbose=True)
```

* train.py GPU memory fix

* ema

* cuda

* cuda

* zeros input

* to device

* batch index 0