* Do not save hyp.yaml and opt.yaml on evolve

* Update general.py

* Export and detect with TensorRT engine file

* Resolve `isort`

* Make validation works with TensorRT engine

* feat: update export docstring

* feat: change suffix from *.trt to *.engine

* feat: get rid of pycuda

* feat: make compatiable with val.py

* feat: support detect with fp16 engine

* Add Lite to Edge TPU string

* Remove *.trt comment

* Revert to standard success logger.info string

* Fix Deprecation Warning

```
export.py:310: DeprecationWarning: Use build_serialized_network instead.
  with builder.build_engine(network, config) as engine, open(f, 'wb') as t:
```

* Revert deprecation warning fix

@imyhxy it seems we can't apply the deprecation warning fix because then export fails, so I'm reverting my previous change here.

* Update export.py

* Update export.py

* Update common.py

* export onnx to file before building TensorRT engine file

* feat: triger ONNX export failed early

* feat: load ONNX model from file
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add feature map to save npy files

Add feature map to save npy files,export npy files with 32 feature maps per layer.

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

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* Update plots.py

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* Update plots.py
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* SECURITY_1.md

* Delete SECURITY.md
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* prune unused imports

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Updated strategy leaves at least 1 cpu free to avoid system overloads. Partially addresses https://github.com/ultralytics/yolov5/issues/5685

* fix tf.py when anchors not equal to 3

* revert the isort fix

* update the fix to use anchor attribute available already

Bumps [pip](https://github.com/pypa/pip) from 19.2 to 21.1.
- [Release notes](https://github.com/pypa/pip/releases)
- [Changelog](https://github.com/pypa/pip/blob/main/NEWS.rst)
- [Commits](https://github.com/pypa/pip/compare/19.2...21.1)

---
updated-dependencies:
- dependency-name: pip
  dependency-type: direct:production
...
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* handle exceptions| attempt CI

* update

* Pre-commit manual run

* yaml one-liner

* Update ci-testing.yml

* Comment W&B CI

Leave as example for future separate CI

* Update ci-testing.yml
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* AutoBatch, AutoAnchor `LOGGER`

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* Update autoanchor.py
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* Fix shuffle DataLoader argument

* Add shuffle argument

* Disable shuffle when rect

* Cleanup, add rect warning

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* Cleanup2

* Cleanup3
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* WORLD_SIZE-safe workers

* Update with DDP comment

@kalenmike per our convo yesterday.

* Improve plots.py robustness

Addresses issues #5374, #5395, #5611

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* `np.unique()` sort fix for segments

* Update datasets.py

Accepts all arguments now by default resolving https://github.com/ultralytics/yolov5/issues/5600

* Update tqdm for fixed width

* Update val.py

* Update val.py

* Try ncols= in train.py

* NCOLS

* NCOLS

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* bar_format

* position 0 leave true

* exp0

* auto

* auto

* Cleanup

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* Cleanup
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* Fix to resource warning allocation; utilize file.open within a context manager

* rename fh to f

in keeping with naming convention
Co-authored-by: Ayman Saleh <aymansaleh@Aymans-MacBook-Pro-2.local>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update __init__.py

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* notebook_init

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* notebook_init

* Created using Colaboratory

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* New `DetectMultiBackend()` class

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* pb to pt fix

* Cleanup

* explicit apply_classifier path

* Cleanup2

* Cleanup3

* Cleanup4

* Cleanup5

* Cleanup6

* val.py MultiBackend inference

* warmup fix

* to device fix

* pt fix

* device fix

* Val cleanup

* COCO128 URL to assets

* half fix

* detect fix

* detect fix 2

* remove half from DetectMultiBackend

* training half handling

* training half handling 2

* training half handling 3

* Cleanup

* Fix CI error

* Add torchscript _extra_files

* Add TorchScript

* Add CoreML

* CoreML cleanup

* New `DetectMultiBackend()` class

* pb to pt fix

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* Cleanup

* explicit apply_classifier path

* Cleanup2

* Cleanup3

* Cleanup4

* Cleanup5

* Cleanup6

* val.py MultiBackend inference

* warmup fix

* to device fix

* pt fix

* device fix

* Val cleanup

* COCO128 URL to assets

* half fix

* detect fix

* detect fix 2

* remove half from DetectMultiBackend

* training half handling

* training half handling 2

* training half handling 3

* Cleanup

* Fix CI error

* Add torchscript _extra_files

* Add TorchScript

* Add CoreML

* CoreML cleanup

* revert default to pt

* Add Usage examples

* Cleanup val
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* Logger consolidation

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Partially addresses invalid mAPs at higher confidence threshold issue https://github.com/ultralytics/yolov5/issues/1466.

* Update detect.py Usage examples

* Inside Ultralytics at https://youtu.be/Zgi9g1ksQHc

* Fix `save_one_box()`

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Fix for Colab hub error:


```python
import yaml

with open('yolov5s.yaml', errors='ignore') as f:
     d = yaml.safe_load(f)  # model dict

print(d)

---------------------------------------------------------------------------
ReaderError                               Traceback (most recent call last)
<ipython-input-8-1150b5143073> in <module>()
      2 
      3 with open('yolov5s.yaml', errors='ignore') as f:
----> 4      d = yaml.safe_load(f)  # model dict
      5 
      6 print(d)

6 frames
/usr/local/lib/python3.7/dist-packages/yaml/reader.py in check_printable(self, data)
    142             position = self.index+(len(self.buffer)-self.pointer)+match.start()
    143             raise ReaderError(self.name, position, ord(character),
--> 144                     'unicode', "special characters are not allowed")
    145 
    146     def update(self, length):

ReaderError: unacceptable character #x1f680: special characters are not allowed
  in "yolov5s.yaml", position 9
```

* Update model yamls for v6.0

* Add python models/yolo.py --test

* Ghost fix

* Update bug-report.yml

* Update question.yml

* Update bug-report.yml

* Update autobatch.py

* Update autobatch.py

* Update autobatch.py

Checking for `onnx_dynamic` first should suppress the warning:

```log
TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
  if self.grid[i].shape[2:4] != x[i].shape[2:4] or self.onnx_dynamic
```

* correct --resume True error

* delete temp file

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