Small polishing changes to DELF code.

Cosmetic changes to spectrogram_to_mel_matrix()

To simplify syncing this c ode back into Google.

Add sanity checks to mel computation.

Clamp the requested frequency range to [0, Nyquist].

PiperOrigin-RevId: 185469605

Update installation.md

Internal changes of object_detection 

185215255  by Zhichao Lu:

    Stop populating image/object/class/text field when generating COCO tf record.

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185213306  by Zhichao Lu:

    Use the params batch size and not the one from train_config in input_fn

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185209081  by Zhichao Lu:

    Handle the case when there are no ground-truth masks for an image.

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185195531  by Zhichao Lu:

    Remove unstack and stack operations on features from third_party/object_detection/model.py.

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185195017  by Zhichao Lu:

    Matrix multiplication based gather op implementation.

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185187744  by Zhichao Lu:

    Fix eval_util minor issue.

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185098733  by Zhichao Lu:

    Internal change

185076656  by Zhichao Lu:

    Increment the amount of boxes for coco17.

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185074199  by Zhichao Lu:

    Add config for SSD Resnet50 v1 with FPN.

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185060199  by Zhichao Lu:

    Fix a bug in clear_detections.
    This method set detection_keys to an empty dictionary instead of an empty set. I've refactored so that this method and the constructor use the same code path.

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185031359  by Zhichao Lu:

    Eval TPU trained models continuously.

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185016591  by Zhichao Lu:

    Use TPUEstimatorSpec for TPU

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185013651  by Zhichao Lu:

    Add PreprocessorCache to record and duplicate augmentations.

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184921763  by Zhichao Lu:

    Minor fixes for object detection.

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184920610  by Zhichao Lu:

    Adds a model builder test for "embedded_ssd_mobilenet_v1" feature extractor.

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184919284  by Zhichao Lu:

    Added unit tests for TPU, with optional training / eval.

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184915910  by Zhichao Lu:

    Update third_party g3 doc with Mask RCNN detection models.

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184914085  by Zhichao Lu:

    Slight change to WeightSharedConvolutionalBoxPredictor implementation to make things match more closely with RetinaNet.  Specifically we now construct the box encoding and class predictor towers separately rather than having them share weights until penultimate layer.

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184913786  by Zhichao Lu:

    Plumbs SSD Resnet V1 with FPN models into model builder.

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184910030  by Zhichao Lu:

    Add coco metrics to evaluator.

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184897758  by Zhichao Lu:

    Merge changes from github.

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184888736  by Zhichao Lu:

    Ensure groundtruth_weights are always 1-D.

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184887256  by Zhichao Lu:

    Introduce an option to add summaries in the model so it can be turned off when necessary.

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184865559  by Zhichao Lu:

    Updating inputs so that a dictionary of tensors is returned from input_fn. Moving unbatch/unpad to model.py.
    Also removing source_id key from features dictionary, and replacing with an integer hash.

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184859205  by Zhichao Lu:

    This CL is trying to hide those differences by making the default settings work with the public code.

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184769779  by Zhichao Lu:

    Pass groundtruth weights into ssd meta architecture all the way to target assigner.

    This will allow training ssd models with padded groundtruth tensors.

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184767117  by Zhichao Lu:

    * Add `params` arg to make all input fns work with TPUEstimator
    * Add --master
    * Output eval results

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184766244  by Zhichao Lu:

    Update create_coco_tf_record to include category indices

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184752937  by Zhichao Lu:

    Create a third_party version of TPU compatible mobilenet_v2_focal_loss coco config.

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184750174  by Zhichao Lu:

    A few small fixes for multiscale anchor generator and a test.

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184746581  by Zhichao Lu:

    Update jupyter notebook to show mask if provided by model.

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184728646  by Zhichao Lu:

    Adding a few more tests to make sure decoding with/without label maps performs as expected.

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184624154  by Zhichao Lu:

    Add an object detection binary for TPU.

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184622118  by Zhichao Lu:

    Batch, transform, and unbatch in the tflearn interface.

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184595064  by Zhichao Lu:

    Add support for training grayscale models.

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184532026  by Zhichao Lu:

    Change dataset_builder.build to perform optional batching using tf.data.Dataset API

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184330239  by Zhichao Lu:

    Add augment_input_data and transform_input_data helper functions to third_party/tensorflow_models/object_detection/inputs.py

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184328681  by Zhichao Lu:

    Use an internal rgb to gray method that can be quantized.

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184327909  by Zhichao Lu:

    Helper function to return padding shapes to use with Dataset.padded_batch.

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184326291  by Zhichao Lu:

    Added decode_func for specialized decoding.

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184314676  by Zhichao Lu:

    Add unstack_batch method to inputs.py.

    This will enable us to convert batched tensors to lists of tensors. This is compatible with OD API that consumes groundtruth batch as a list of tensors.

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184281269  by Zhichao Lu:

    Internal test target changes.

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184192851  by Zhichao Lu:

    Adding `Estimator` interface for object detection.

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184187885  by Zhichao Lu:

    Add config_util functions to help with input pipeline.

    1. function to return expected shapes from the resizer config
    2. function to extract image_resizer_config from model_config.

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184139892  by Zhichao Lu:

    Adding support for depthwise SSD (ssd-lite) and depthwise box predictions.

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184089891  by Zhichao Lu:

    Fix third_party faster rcnn resnet101 coco config.

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184083378  by Zhichao Lu:

    In the case when there is no object/weights field in tf.Example proto, return a default weight of 1.0 for all boxes.

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PiperOrigin-RevId: 185215255

Explicitly specify checkpoint version.

Fix simple errors in synthetic examples in lfads.

change to lfads to allow training of encoder weights only

TF Saver now requires specifying the checkpoint version even when restoring to avoid errors when we specify
a path to a checkpoint file instead of a directory.

change to lfads to allow training of encoder weights only

Update generate_cifar10_tfrecords.py

The change you added did not work with python2, it does not have encoding in .log.  This fixes it. feel free to test on Python3.  I tested python2 and I am really sue this works fine for python3.  Good catch.  sorry for not having it fixed earlier.

Allow users to pass in num_classes to ResNet

Fix mnist_tpu.py which was giving unknown shape errors

Add a note about tf.image.convert_image_dtype

Update ISSUE_TEMPLATE.md

Return datasets directly from input_fns for TF1.5

change cPickle to pickle for python3
specify  encoding='latin1' when call pickle.load()

Use the short path for TPUClusterResolver

The long path doesn't work for TensorFlow 1.6 because the .python package under cluster_resolver doesn't exist.

Add ClusterResolver capability to mnist_tpu.py

* Refactoring input function

* Updating name of variable