Fix for memory model run() function to run in car application without passing previous steering/throttle values (#922)

Switched history vector to deque for performance

* Dispatch between augmentations which change the training data and transformations, like multiply and crop which manipulate the images in training, validation and inferencing (driving).
* Adding trapeze / crop arguments to configs and car app
* Improve UI text in train screen
* Improve logging augmentations and tests
* Added training test with augmentation
* Fix model types in basic.py (only name the first few...)
* Rename augmentation interface to `run` so it can be used as a part. Remove obsolete Augmentations part.
* Simplified blur/brightness augmentations in UI
* Add support for cropping and trapezoidal transformation in UI.

Co-authored-by: TCIII <thomascoyle11859@gmail.com>

overdrive change status: recording=False when delete button pushed. add valiadtion limit to avoid keras memory leak. large dataset support.

1.  fix the bugs originated from the latest commit b544241f (Add support for all other (except KerasLatent) models: (autorope#884))

2.  improve the approach for calculating saliency maps,
2.1 evaluate the effects of all output layers instead of one
2.2 correct the problematic math (blending the gradients of angle and throttle output layers together) from direct sum to square norm
2.3 calculate the saliency depending on the model type "linear" and "categorical"

3.  modify the "draw_user_input", "draw_model_prediction", and "draw_steering_distribution" methods, seperate the image array for inference and the image array that labels are drawn on

Put golden source of version into module's __init__.py so versions are in sync with setup.up. (#902)

https://github.com/autorope/donkeycar/pull/900 1. fix the bugs originated from the latest commit b544241f

* Restored approved RC control changes

* Reverted to RC control changes

* Merged in OLED resolution changes

* Added back in OLED resolution

* Factor out model from interpreter so each model can be saved and run in .h5 / .savedmodel keras format, in tflite format or in tensorrt format
* Improved KerasPilot interfaces to support the above
* Added test for all models and all interpreters (TFflite excluded for 3d CNN and TRT excluded for LSTM as these are not supported respectively)
* use expand_dims and squeeze instead of reshape and [0]

UI improvements:
* Add support for all model / interpreter combinations in training and model arena
* Add options to sync only h5, savedmodel, tflite or tensorrt pilots to car
* Fixed disabling of keyboard when switching from one screen to another

Small improvements / fixes:
* Added comment to status in train screen
* Added better error message in trt conversion
* Added seq length to lstm model str
* Added shebang to profile.py

Change on models:
* Convert LSTM and 3D-CNN model from Sequential to Functional form, because transfer learning, i.e. continuing to train an already trained model, only works in the functional form of these two models.
* Added new model KerasLinearMemory which reads in the last n actions, this facilitates smoother steering
* Added support to inference from dictionary - passing by dictionary is used in training and supports augmentation
* Renamed output layers alphabetically in order to avoid tflite bug which returns output tensors in that order

General code changes:
* Add Collator class which returns list of continuous records so sequence models, like rnn, 3dcnn, memory can be trained. Add test.
* Add comparison string class (called EqMemorizedString) to better manage printing available user options. Used in get_model_by_type.
* Reduced tolerance on keras test as we still see relative differences of 2e-5 (which is ok).
* Check either relative or absolute tolerance as untrained models might return values >> 1 in keras test

- tf2 version incomplatibility
- uint8 conversion bug

* Add OLED resolution option

* Add OLED resolution option

* Addressed code review

* WIP

* Fixed web server

* Got the basics woprking

* Fixed some logic, trapped some error conditions

Also changed "SERVO_ESC" drivetrain type, which doesn't really mean anything, to "I2C_SERVO", which actually describes the board used

* removed RC class stub

* Basic port done

* cleanup

* Fixed mode switch

* Fixed joystick import issue

* Changed option name to "PIGPIO_RC" which is more clear

* changed rc controller option config to "pigpio_rc"

* typo

* Fixed comment to align with nomenclature

* Fixed auto-record on throttle

Did a little other cleanup

* Cosmetic cleanup per review

* Fixed auto-record so it is only on when desired

Did some other cleanup of unneeded constants and added a debug option

* Changes per review

* WIP

Fixed web server

Got the basics woprking

Fixed some logic, trapped some error conditions

Also changed "SERVO_ESC" drivetrain type, which doesn't really mean anything, to "I2C_SERVO", which actually describes the board used

removed RC class stub

Basic port done

cleanup

Fixed mode switch

Fixed joystick import issue

Changed option name to "PIGPIO_RC" which is more clear

changed rc controller option config to "pigpio_rc"

typo

Fixed comment to align with nomenclature

Fixed auto-record on throttle

Did a little other cleanup

Cosmetic cleanup per review

Fixed auto-record so it is only on when desired

Did some other cleanup of unneeded constants and added a debug option

Changes per review

* Addressed code review

Co-authored-by: Chris Anderson <gca2@earthlink.net>

Revert to passing full path to model in training call which got accidentally broken in 4.2 master. (#873)

* Fix delete_last_n_records in tub.
* Pep-8: remove whitespace
* Add test.

* Update to CircuitPython OLED library

* Per code review

* Added the OLED library to Nano installation, too

Co-authored-by: Chris Anderson <gca2@earthlink.net>