GitLab

* Merged commit includes the following changes:
257930561  by yongzhe:

    Mobile LSTD TfLite Client.

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257928126  by yongzhe:

    Mobile SSD Tflite client.

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257921181  by menglong:

    Fix discrepancy between pre_bottleneck = {true, false}

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257561213  by yongzhe:

    File utils.

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257449226  by yongzhe:

    Mobile SSD Client.

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257264654  by yongzhe:

    SSD utils.

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257235648  by yongzhe:

    Proto bazel build rules.

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256437262  by Menglong Zhu:

    Fix check for FusedBatchNorm op to only verify it as a prefix.

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256283755  by yongzhe:

    Bazel build and copybara changes.

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251947295  by yinxiao:

    Add missing interleaved option in checkpoint restore.

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251513479  by yongzhe:

    Conversion utils.

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248783193  by yongzhe:

    Branch protos needed for the lstd client.

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248200507  by menglong:

    Fix proto namespace in example config

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PiperOrigin-RevId: 257930561

* Delete BUILD

* Initial implementation of Shakespeare character LSTM.

* Fix import order

257883986  by hongkuny<hongkuny@google.com>:

    Adds tf.summary for bert training

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PiperOrigin-RevId: 257883986

257914648  by lzc:

    Internal changes

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257525973  by Zhichao Lu:

    Fixes bug that silently prevents checkpoints from loading when training w/ eager + functions. Also sets up scripts to run training.

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257296614  by Zhichao Lu:

    Adding detection_features to model outputs

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257234565  by Zhichao Lu:

    Fix wrong order of `classes_with_max_scores` in class-agnostic NMS caused by
    sorting in partitioned-NMS.

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257232002  by ronnyvotel:

    Supporting `filter_nonoverlapping` option in np_box_list_ops.clip_to_window().

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257198282  by Zhichao Lu:

    Adding the focal loss and l1 loss from the Objects as Points paper.

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257089535  by Zhichao Lu:

    Create Keras based ssd + resnetv1 + fpn.

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257087407  by Zhichao Lu:

    Make object_detection/data_decoders Python3-compatible.

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257004582  by Zhichao Lu:

    Updates _decode_raw_data_into_masks_and_boxes to the latest binary masks-to-string encoding format.

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257002124  by Zhichao Lu:

    Make object_detection/utils Python3-compatible, except json_utils.

    The patching trick used in json_utils is not going to work in Python 3.

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256795056  by lzc:

    Add a detection_anchor_indices field to detection outputs.

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256477542  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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256387593  by Zhichao Lu:

    Edit class_id_function_approximations builder to skip class ids not present in label map.

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256259039  by Zhichao Lu:

    Move NMS to TPU for FasterRCNN.

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256071360  by rathodv:

    When multiclass_scores is empty, add one-hot encoding of groundtruth_classes as multiclass scores so that data_augmentation ops that expect the presence of multiclass_scores don't have to individually handle this case.

    Also copy input tensor_dict to out_tensor_dict first to avoid inplace modification.

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256023645  by Zhichao Lu:

    Adds the first WIP iterations of TensorFlow v2 eager + functions style custom training & evaluation loops.

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255980623  by Zhichao Lu:

    Adds a new data augmentation operation "remap_labels" which remaps a set of labels to a new label.

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255753259  by Zhichao Lu:

    Announcement of the released evaluation tutorial for Open Images Challenge
    2019.

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255698776  by lzc:

    Fix rewrite_nn_resize_op function which was broken by tf forward compatibility movement.

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255623150  by Zhichao Lu:

    Add Keras-based ResnetV1 models.

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255504992  by Zhichao Lu:

    Fixing the typo in specifying label expansion for ground truth segmentation
    file.

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255470768  by Zhichao Lu:

    1. Fixing Python bug with parsed arguments.
    2. Adding capability to parse relevant columns from CSV header.
    3. Fixing bug with duplicated labels expansion.

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255462432  by Zhichao Lu:

    Adds a new data augmentation operation "drop_label_probabilistically" which drops a given label with the given probability. This supports experiments on training in the presence of label noise.

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255441632  by rathodv:

    Fallback on groundtruth classes when multiclass_scores tensor is empty.

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255434899  by Zhichao Lu:

    Ensuring evaluation binary can run even with big files by synchronizing
    processing of ground truth and predictions: in this way, ground truth is not stored but immediatly
    used for evaluation. In case gt of object masks, this allows to run
    evaluations on relatively large sets.

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255337855  by lzc:

    Internal change.

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255308908  by Zhichao Lu:

    Add comment to clarify usage of calibration parameters proto.

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255266371  by Zhichao Lu:

    Ensuring correct processing of the case, when no groundtruth masks are provided
    for an image.

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255236648  by Zhichao Lu:

    Refactor model_builder in faster_rcnn.py to a util_map, so that it's possible to be overwritten.

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255093285  by Zhichao Lu:

    Updating capability to subsample data during evaluation

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255081222  by rathodv:

    Convert groundtruth masks to be of type float32 before its used in the loss function.

    When using mixed precision training, masks are represented using bfloat16 tensors in the input pipeline for performance reasons. We need to convert them to float32 before using it in the loss function.

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254788436  by Zhichao Lu:

    Add forward_compatible to non_max_suppression_with_scores to make it is
    compatible with older tensorflow version.

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254442362  by Zhichao Lu:

    Add num_layer field to ssd feature extractor proto.

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253911582  by jonathanhuang:

    Plumbs Soft-NMS options (using the new tf.image.non_max_suppression_with_scores op) into the TF Object Detection API.  It adds a `soft_nms_sigma` field to the postprocessing proto file and plumbs this through to both the multiclass and class_agnostic versions of NMS. Note that there is no effect on behavior of NMS when soft_nms_sigma=0 (which it is set to by default).

    See also "Soft-NMS -- Improving Object Detection With One Line of Code" by Bodla et al (https://arxiv.org/abs/1704.04503)

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253703949  by Zhichao Lu:

    Internal test fixes.

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253151266  by Zhichao Lu:

    Fix the op type check for FusedBatchNorm, given that we introduced
    FusedBatchNormV3 in a previous change.

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252718956  by Zhichao Lu:

    Customize activation function to enable relu6 instead of relu for saliency
    prediction model seastarization

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252158593  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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252150717  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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251967048  by Zhichao Lu:

    Make GraphRewriter proto extensible.

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251950039  by Zhichao Lu:

    Remove experimental_export_device_assignment from TPUEstimator.export_savedmodel(), so as to remove rewrite_for_inference().

    As a replacement, export_savedmodel() V2 API supports device_assignment where user call tpu.rewrite in model_fn and pass in device_assigment there.

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251890697  by rathodv:

    Updated docstring to include new output nodes.

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251662894  by Zhichao Lu:

    Add autoaugment augmentation option to objection detection api codebase. This
    is an available option in preprocessor.py.

    The intended usage of autoaugment is to be done along with random flipping and
    cropping for best results.

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251532908  by Zhichao Lu:

    Add TrainingDataType enum to track whether class-specific or agnostic data was used to fit the calibration function.

    This is useful, since classes with few observations may require a calibration function fit on all classes.

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251511339  by Zhichao Lu:

    Add multiclass isotonic regression to the calibration builder.

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251317769  by pengchong:

    Internal Change.

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250729989  by Zhichao Lu:

    Fixing bug in gt statistics count in case of mask and box annotations.

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250729627  by Zhichao Lu:

    Label expansion for segmentation.

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250724905  by Zhichao Lu:

    Fix use_depthwise in fpn and test it with fpnlite on ssd + mobilenet v2.

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250670379  by Zhichao Lu:

    Internal change

250630364  by lzc:

    Fix detection_model_zoo footnotes

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250560654  by Zhichao Lu:

    Fix static shape issue in matmul_crop_and_resize.

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250534857  by Zhichao Lu:

    Edit class agnostic calibration function docstring to more accurately describe the function's outputs.

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250533277  by Zhichao Lu:

    Edit the multiclass messages to use class ids instead of labels.

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PiperOrigin-RevId: 257914648

* Record highest uncased bleu found.

* change to bleu_best_score_iteration

257314238  by hongkuny<hongkuny@google.com>:

    Creates transformer v2 README.
    Remove contents that are not implemented.

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PiperOrigin-RevId: 257314238

* Move to global_step.

* Hook to use global_step.

* fix comment start step 1 not step 0.

* remove hack used for testing.

* Add docstring.

* Update research/maskgan/README.md
Co-Authored-By: Andrew M Dai <andy.dai@gmail.com>

* Improve performance for Cifar ResNet benchmarks

* Revert batch size changes to benchmarks

Update to tf 1.14 syntax, fix bug #7125 (needed additional expand for conv2d).  Suppress compat warnings by moving to compat.v1 versions of some functions.  Note that this code is not 2.0 compatible yet - that will be a future push. (#7177)

* reduce iterations from 20 to 12.

* add fp16 dynamic batch accuracy check.

* fix existing lint issue.

* Bug fix of cifar10_eval.py

line 120: changed from eval_data = FLAGS.eval_data == 'test'
to: eval_data = FLAGS.eval_data
comment: the original code assigns 'true' to eval_data, when the script is being used to evaluate networks on the evaluation set, it DOES NOT load the evaluation set as intended, but actually loads the trainning set (line 105 of cifar10_input.py).

* Remove one line that was an artifact of issue.

* Fix unit tests failures.

* 96% of TF 2.0 tests on GPU are passing.

* Currently all passing GPU and CPU TF 2.0

* Address code comments.

* use tf 2.0 cast.

* Comment about working on TF 2.0 CPU

* Uses contrib turn off for TF 2.0.

* Fix wide_deep and add keras_common_tests.

* use context to get num_gpus.

* Switch to tf.keras.metrics

256204636  by hongkuny<hongkuny@google.com>:

    Internal

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256079834  by hongkuny<hongkuny@google.com>:

    Clean up: move common flags together for further refactoring
    Enable steps_per_loop option for all applications.

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PiperOrigin-RevId: 256204636

* Add StepCounterHook to hooks_helper.py

* Update symbol.

when there are multiple workers.

* borrowing a tf1.x optimization which converts gradients from sparse to dense for better perf

* cleanup after code review

* Merged commit includes the following changes:
255493073  by hongkuny<hongkuny@google.com>:

    BERT initial OSS readme update.

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255470372  by dmchen<dmchen@google.com>:

    Slightly expand expected range for F1 score in BERT SQuAD accuracy test

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255109240  by hongkuny<hongkuny@google.com>:

    Update eval/predict batch sizes.

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255010016  by hongkuny<hongkuny@google.com>:

    Internal

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254874613  by hongkuny<hongkuny@google.com>:

    Update glue tasks enum to match directory name

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254866171  by taylorrobie<taylorrobie@google.com>:

    Internal change

254785517  by zongweiz<zongweiz@google.com>:

    Use train_single_step for BERT GPU models to temporarily work around some performance bugs in GPU runs

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254497647  by hongkuny<hongkuny@google.com>:

    Fix device placement for TPU export model.

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PiperOrigin-RevId: 255493073

* Update README.md

255493073  by hongkuny<hongkuny@google.com>:

    BERT initial OSS readme update.

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255470372  by dmchen<dmchen@google.com>:

    Slightly expand expected range for F1 score in BERT SQuAD accuracy test

--
255109240  by hongkuny<hongkuny@google.com>:

    Update eval/predict batch sizes.

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255010016  by hongkuny<hongkuny@google.com>:

    Internal

--

PiperOrigin-RevId: 255493073

254874613  by hongkuny<hongkuny@google.com>:

    Update glue tasks enum to match directory name

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254866171  by taylorrobie<taylorrobie@google.com>:

    Internal change

PiperOrigin-RevId: 254874613

254785517  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Use train_single_step for BERT GPU models to temporarily work around some performance bugs in GPU runs

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254497647  by hongkuny<hongkuny@google.com>:

    Fix device placement for TPU export model.

--

PiperOrigin-RevId: 254785517

* restored missing function

* missing import

* missing imports

* updated tutorial link

* recovered _print_download_progress func

* change default train with float16 instead of float32 accuracy

* test disable func call

* redundant function call, currently data is pulled automatically in

* optimized imports

* optimized imports

* trying fake merge call

* make metrics optional

* Remove extra print

* cpu benchmark and accuracy tests.

* add docstrings to fix lint.

* XLA FP32 and first test

* More XLA benchmarks FP32.

* Add eager to NCF and refactor resnet.

* fix v2_0 calls and more flag refactor.

* Remove extra flag args.

* 90 epoch default

* add return

* remove xla not used by estimator.

* Remove duplicate run_eagerly.

* fix flag defaults.

* Remove fp16_implementation flag option.

* Remove stop early on mlperf test.

* remove unneeded args.

* load flags from keras mains.

254134531  by yuefengz<yuefengz@google.com>:

    Fix a typo in bert_benchmark.py

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PiperOrigin-RevId: 254134531