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* Merged commit includes the following changes:
207771702  by Zhichao Lu:

    Refactoring evaluation utilities so that it is easier to introduce new DetectionEvaluators with eval_metric_ops.

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207758641  by Zhichao Lu:

    Require tensorflow version 1.9+ for running object detection API.

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207641470  by Zhichao Lu:

    Clip `num_groundtruth_boxes` in pad_input_data_to_static_shapes() to `max_num_boxes`. This prevents a scenario where tensors are sliced to an invalid range in model_lib.unstack_batch().

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207621728  by Zhichao Lu:

    This CL adds a FreezableBatchNorm that inherits from the Keras BatchNormalization layer, but supports freezing the `training` parameter at construction time instead of having to do it in the `call` method.

    It also adds a method to the `KerasLayerHyperparams` class that will build an appropriate FreezableBatchNorm layer according to the hyperparameter configuration. If batch_norm is disabled, this method returns and Identity layer.

    These will be used to simplify the conversion to Keras APIs.

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207610524  by Zhichao Lu:

    Update anchor generators and box predictors for python3 compatibility.

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207585122  by Zhichao Lu:

    Refactoring convolutional box predictor into separate prediction heads.

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207549305  by Zhichao Lu:

    Pass all 1s for batch weights if nothing is specified in GT.

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207336575  by Zhichao Lu:

    Move the new argument 'target_assigner_instance' to the end of the list of arguments to the ssd_meta_arch constructor for backwards compatibility.

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207327862  by Zhichao Lu:

    Enable support for float output in quantized custom op for postprocessing in SSD Mobilenet model.

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207323154  by Zhichao Lu:

    Bug fix: change dict.iteritems() to dict.items()

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207301109  by Zhichao Lu:

    Integrating expected_classification_loss_under_sampling op as an option in the ssd_meta_arch

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207286221  by Zhichao Lu:

    Adding an option to weight regression loss with foreground scores from the ground truth labels.

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207231739  by Zhichao Lu:

    Explicitly mentioning the argument names when calling the batch target assigner.

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207206356  by Zhichao Lu:

    Add include_trainable_variables field to train config to better handle trainable variables.

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207135930  by Zhichao Lu:

    Internal change.

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206862541  by Zhichao Lu:

    Do not unpad the outputs from batch_non_max_suppression before sampling.

    Since BalancedPositiveNegativeSampler takes an indicator for valid positions to sample from we can pass the output from NMS directly into Sampler.

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PiperOrigin-RevId: 207771702

* Remove unused doc.