datascienceinc / Skater / 342 / 2
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Updating the repo with more examples and bug fixes in-regards to recent changes(#233)

* starting on a new branch to resolve recent build failures on compute_relevance_dev

* transferring changes in image_ops from previous dev branch

* reverting files from the last commit to trace the cause of the failure

* reverting files to resolve build issue

* moving ahead cautiously with other files

* adjusting imports as suggested online to resolve static TLS

* this issue seems to be occurring for other libraries as well, will have to look into it later(#229)

* adding a try catch around the import of BRLC

* resolving flake8 related issue

* adding all other remaining changes related to inferring with perturbation

* some what working code for perturbation based inference

* attempting to simplify the implementation

* working version of feature perturbation using occlusion

* correcting the build error because of the assertion

* handling passing of optional arguments for perturbation based methods

* enabled ability to customize window_size and step_size for perturbing feature space with occlusion; improved unit tests

* resolving build error related to rolling window changes

* resolving minor code error, causing build issues

* this should resolve build errors

* resolving missedout flake8 indendation error

* all .ipynb notebooks updated, minor logging improvements to perturbation_relevance_scorer.py

* resolving last minute flake8 error

* improving code quality, removed unused imports and better initialization of variables

* correcting a logical error in assigning baseline for computing relevance/attribution

* code improvement, handling exceptions for third party imports(matplotlib)

* minor correcting in the function signature of _enable_axis

* adding a simple toy example of applying skater to model predicting steering angle

* updating self driving toy examples and modification to test_image... (continued)

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Source Files on job 342.2