GitLab

* Adding option for one_box_for_all_classes to the box_predictor

PiperOrigin-RevId: 192813444

* Extend to accept different ratios of conv channels.

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* Remove inaccurate caveat from proto file.

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* Add option to set dropout for classification net in weight shared box predictor.

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* fix flakiness in testSSDRandomCropWithMultiClassScores due to randomness.

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* Post-process now works again in train mode.

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* Adding support for reading in logits as groundtruth labels and applying an optional temperature (scaling) before softmax in support of distillation.

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* Add a util function to visualize value histogram as a tf.summary.image.

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* Do not add batch norm parameters to final conv2d ops that predict boxes encodings and class scores in weight shared conv box predictor.

This allows us to set proper bias and force initial predictions to be background when using focal loss.

PiperOrigin-RevId: 193204364

* Make sure the final layers are also resized proportional to conv_depth_ratio.

PiperOrigin-RevId: 193228972

* Remove deprecated batch_norm_trainable field from ssd mobilenet v2 config

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* Updating coco evaluation metrics to allow for a batch of image info, rather than a single image.

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* Update protobuf requirements to 3+ in installation docs.

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* Add support for training keypoints.

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* Fix data augmentation functions.

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* Read the default batch size from config file.

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* Fixing a bug in the coco evaluator.

PiperOrigin-RevId: 193974479

* num_gt_boxes_per_image and num_det_boxes_per_image value incorrect.
Should be not the expand dim.

PiperOrigin-RevId: 194122420

* Add option to evaluate any checkpoint (without requiring write access to that directory and overwriting any existing logs there).

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* PiperOrigin-RevId: 190346687

* - Expose slim arg_scope function to compute keys to enable tessting.
- Add is_training=None option to mobinenet arg_scopes. This allows the users to set is_training from an outer scope.

PiperOrigin-RevId: 190997959

* Add an option to not set slim arg_scope for batch_norm is_training parameter. This enables users to set the is_training parameter from an outer scope.

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Increase minimum TF version for DEFINE_enum and rename variable mappings for change to RNN variable names. (#4123)

* + 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

PiperOrigin-RevId: 192624207

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).

PiperOrigin-RevId: 192320460

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PiperOrigin-RevId: 192006190

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

PiperOrigin-RevId: 192004845

PiperOrigin-RevId: 191957195

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

PiperOrigin-RevId: 191932855

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.

PiperOrigin-RevId: 191787921