GitLab

* + plot_partition.py (budget allocation with smooth sensitivity).
+ utility_queries_answered.py (Figure 1, left).
+ several changes to the scripts required for the ICLR poster.

* Adding Ananth Raghunathan (pseudorandom@) to the list of owners of differential_privacy.

* Fixing the owners list of differential_privacy.

* Add minigo unit test

* Add minigo unit test

* Fix gpylints and update readme

* Add minigo

* Fix comments and make python version compatible

* Fix TensorRT test output and add int8 result.

* Fix comments

* Removing footnote declaration as well

* fix issue 'could not satisfy explicit device'

* remove the line unrelated to fix issue

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image evaluation).

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Returning eval_on_train_input_fn from create_estimator_and_inputs(), rather than using train_input_fn in EVAL mode (which will still have data augmentation).

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Migrating away from Experiment class, as it is now deprecated. Also, refactoring into a separate model library and binaries.

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Add an option to skip the last striding in mobilenet. The modified network has nominal output stride 16 instead of 32.

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Add option to override base feature extractor hyperparams in SSD models. This would allow us to use the same set of hyperparams for the complete feature extractor (base + new layers) if desired.

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Adding an attribute to SSD model to indicate which fields in prediction dictionary have a batch dimension. This will be useful for future video models.

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The current code does not work in py2 since the input string could
contain unicode string, and default encoding in ASCII in py2. Change
the method to only do encode() which convert string to byte array
when running python3.

* Adding cast to fp32

* Adding myself to OWNERS

duplicate eval metric: change the fourth metric from ## Weighted PASCAL VOC detection metric to ##  Weighted PASCAL VOC instance segmentation metric .