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* forbid resnet v1 fp16

* address PR comments

Updates to differential_privacy/pate following the Banff workshop.

Collapse license cell

Fix typo in iris_data.py

* Add run individual step only option

* Fix comments and update readme

* Add valiation argument

* Address comments

* Make code shorter

* Fix more lints

* rename --version flag and fix tests to correctly specify version rather than verbosity

* rename version to resnet_version throughout

* fix bugs

* delint

* missed layer_test

* fix indent

* Add dataset info and hyper parameter logging for benchmark.

* Address review comments.

* Address the view comment for data schema name.

* Fix test cases.

* Lint fix.

Internal changes to object detection

195269567  by Zhichao Lu:

    Removing image summaries during train mode.

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195147413  by Zhichao Lu:

    SSDLite config for mobilenet v2.

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194883585  by Zhichao Lu:

    Simplify TPU compatible nearest neighbor upsampling using reshape and broadcasting.

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194851009  by Zhichao Lu:

    Include ava v2.1 detection models in model zoo.

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194292198  by Zhichao Lu:

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

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194122420  by Zhichao Lu:

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

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193974479  by Zhichao Lu:

    Fixing a bug in the coco evaluator.

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193959861  by Zhichao Lu:

    Read the default batch size from config file.

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193737238  by Zhichao Lu:

    Fix data augmentation functions.

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193576336  by Zhichao Lu:

    Add support for training keypoints.

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193409179  by Zhichao Lu:

    Update protobuf requirements to 3+ in installation docs.

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193382651  by Zhichao Lu:

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

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193244778  by Zhichao Lu:

    Remove deprecated batch_norm_trainable field from ssd mobilenet v2 config

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193228972  by Zhichao Lu:

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

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193204364  by Zhichao Lu:

    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.

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193137342  by Zhichao Lu:

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

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193119411  by Zhichao Lu:

    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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193087707  by Zhichao Lu:

    Post-process now works again in train mode.

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193067658  by Zhichao Lu:

    fix flakiness in testSSDRandomCropWithMultiClassScores due to randomness.

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192922089  by Zhichao Lu:

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

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192850747  by Zhichao Lu:

    Remove inaccurate caveat from proto file.

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192837477  by Zhichao Lu:

    Extend to accept different ratios of conv channels.

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192813444  by Zhichao Lu:

    Adding option for one_box_for_all_classes to the box_predictor

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192624207  by Zhichao Lu:

    Update to trainer to allow for reading multiclass scores

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192583425  by Zhichao Lu:

    Contains implementation of Visual Relations Detection evaluation metric (per
    image evaluation).

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192529600  by Zhichao Lu:

    Modify the ssd meta arch to allow the option of not adding an implicit background class.

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192512429  by Zhichao Lu:

    Refactor model_tpu_main.py files and move continuous eval loop into model_lib.py

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192494267  by Zhichao Lu:

    Update create_pascal_tf_record.py and create_pet_tf_record.py

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192485456  by Zhichao Lu:

    Enforcing that all eval metric ops have valid python strings.

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192472546  by Zhichao Lu:

    Set regularize_depthwise to true in mobilenet_v1_argscope.

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192421843  by Zhichao Lu:

    Refactoring of Mask-RCNN to put all mask prediction code in third stage.

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192320460  by Zhichao Lu:

    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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192226678  by Zhichao Lu:

    Access TPUEstimator and CrossShardOptimizer from tf namesspace.

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192195514  by Zhichao Lu:

    Fix test that was flaky due to randomness

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192166224  by Zhichao Lu:

    Minor fixes to match git repo.

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192147130  by Zhichao Lu:

    use shape utils for assertion in feature extractor.

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192132440  by Zhichao Lu:

    Class agnostic masks for mask_rcnn

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192006190  by Zhichao Lu:

    Add learning rate summary in EVAL mode in model.py

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192004845  by Zhichao Lu:

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

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191957195  by Zhichao Lu:

    Add classification_loss and localiztion_loss metrics for TPU jobs.

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191932855  by Zhichao Lu:

    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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191787921  by Zhichao Lu:

    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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191743097  by Zhichao Lu:

    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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191668425  by Zhichao Lu:

    Internal change.

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191649512  by Zhichao Lu:

    Introduce two parameters in ssd.proto - freeze_batchnorm, inplace_batchnorm_update - and set up slim arg_scopes in ssd_meta_arch.py such that applies it to all batchnorm ops in the predict() method.

    This centralizes the control of freezing and doing inplace batchnorm updates.

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191620303  by Zhichao Lu:

    Modifications to the preprocessor to support multiclass scores

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PiperOrigin-RevId: 195269567

* Revert 823da318. This restores distribution strategies for resnet.

This commit is not a direct revert due to significant merge conflict
resolution.

* fix flags test

* npc is no longer used in resnet

* fix treatment of main() and absl flags

* add mnist_eager, and delint

* add mnist_eager docstring

* squash of modular absl usage commits

* delint

* address PR comments

* change hooks to comma separated list, as absl behavior for space separated lists is not as expected

Add buttons and enable TOC

official/mnist: Updates with the release of TensorFlow 1.8.

* Adding option for one_box_for_all_classes to the box_predictor

PiperOrigin-RevId: 192813444

* Extend to accept different ratios of conv channels.

PiperOrigin-RevId: 192837477

* Remove inaccurate caveat from proto file.

PiperOrigin-RevId: 192850747

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

PiperOrigin-RevId: 192922089

* fix flakiness in testSSDRandomCropWithMultiClassScores due to randomness.

PiperOrigin-RevId: 193067658

* Post-process now works again in train mode.

PiperOrigin-RevId: 193087707

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

PiperOrigin-RevId: 193119411

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

PiperOrigin-RevId: 193137342

* 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

PiperOrigin-RevId: 193244778

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

PiperOrigin-RevId: 193382651

* Update protobuf requirements to 3+ in installation docs.

PiperOrigin-RevId: 193409179

* Add support for training keypoints.

PiperOrigin-RevId: 193576336

* Fix data augmentation functions.

PiperOrigin-RevId: 193737238

* Read the default batch size from config file.

PiperOrigin-RevId: 193959861

* 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).

PiperOrigin-RevId: 194292198

* 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.

PiperOrigin-RevId: 191611934

* PiperOrigin-RevId: 191955231

* PiperOrigin-RevId: 193254125

* PiperOrigin-RevId: 193371562

* PiperOrigin-RevId: 194085628

* catch cpuinfo ImportError

* add psutil import catch

* fix typo

[samples/core/get_starter/eager]: Update with API simplifications in 1.8

Add marco model: automating the evaluation of crystallization experiments