GitLab

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

247226201  by ronnyvotel:

    Updating the visualization tools to accept unique_ids for color coding.

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247067830  by Zhichao Lu:

    Add box_encodings_clip_range options for the convolutional box predictor (for TPU compatibility).

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246888475  by Zhichao Lu:

    Remove unused _update_eval_steps function.

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246163259  by lzc:

    Add a gather op that can handle ignore indices (which are "-1"s in this case).

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246084944  by Zhichao Lu:

    Keras based implementation for SSD + MobilenetV2 + FPN.

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245544227  by rathodv:

    Add batch_get_targets method to target assigner module to gather any groundtruth tensors based on the results of target assigner.

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245540854  by rathodv:

    Update target assigner to return match tensor instead of a match object.

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245434441  by Zhichao Lu:

    Add README for tpu_exporters package.

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245381834  by lzc:

    Internal change.

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245298983  by Zhichao Lu:

    Add conditional_shape_resizer to config_util

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245134666  by Zhichao Lu:

    Adds ConditionalShapeResizer to the ImageResizer proto which enables resizing only if input image height or width is is greater or smaller than a certain size. Also enables specification of resize method in resize_to_{max, min}_dimension methods.

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245093975  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (faster-rcnn)

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245072421  by Zhichao Lu:

    Adds a new image resizing method "resize_to_max_dimension" which resizes images only if a dimension is greater than the maximum desired value while maintaining aspect ratio.

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244946998  by lzc:

    Internal Changes.

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244943693  by Zhichao Lu:

    Add a custom config to mobilenet v2 that makes it more detection friendly.

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244754158  by derekjchow:

    Internal change.

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244699875  by Zhichao Lu:

    Add check_range=False to box_list_ops.to_normalized_coordinates when training
    for instance segmentation.  This is consistent with other calls when training
    for object detection.  There could be wrongly annotated boxes in the dataset.

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244507425  by rathodv:

    Support bfloat16 for ssd models.

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244399982  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd)

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244209387  by Zhichao Lu:

    Internal change.

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243922296  by rathodv:

    Change `raw_detection_scores` to contain softmax/sigmoid scores (not logits) for `raw_ detection_boxes`.

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243883978  by Zhichao Lu:

    Add a sample fully conv config.

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243369455  by Zhichao Lu:

    Fix regularization loss gap in Keras and Slim.

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243292002  by lzc:

    Internal changes.

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243097958  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd model)

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243007177  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd model)

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242776550  by Zhichao Lu:

    Make object detection pre-processing run on GPU.  tf.map_fn() uses
    TensorArrayV3 ops, which have no int32 GPU implementation.  Cast to int64,
    then cast back to int32.

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242723128  by Zhichao Lu:

    Using sorted dictionaries for additional heads in non_max_suppression to ensure tensor order

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242495311  by Zhichao Lu:

    Update documentation to reflect new TFLite examples repo location

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242230527  by Zhichao Lu:

    Fix Dropout bugs for WeightSharedConvolutionalBoxPred.

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242226573  by Zhichao Lu:

    Create Keras-based WeightSharedConvolutionalBoxPredictor.

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241806074  by Zhichao Lu:

    Add inference in unit tests of TFX OD template.

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241641498  by lzc:

    Internal change.

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241637481  by Zhichao Lu:

    matmul_crop_and_resize(): Switch to dynamic shaping, so that not all dimensions are required to be known.

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241429980  by Zhichao Lu:

    Internal change

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241167237  by Zhichao Lu:

    Adds a faster_rcnn_inception_resnet_v2 Keras feature extractor, and updates the model builder to construct it.

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241088616  by Zhichao Lu:

    Make it compatible with different dtype, e.g. float32, bfloat16, etc.

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240897364  by lzc:

    Use image_np_expanded in object_detection_tutorial notebook.

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240890393  by Zhichao Lu:

    Disable multicore inference for OD template as its not yet compatible.

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240352168  by Zhichao Lu:

    Make SSDResnetV1FpnFeatureExtractor not protected to allow inheritance.

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240351470  by lzc:

    Internal change.

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239878928  by Zhichao Lu:

    Defines Keras box predictors for Faster RCNN and RFCN

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239872103  by Zhichao Lu:

    Delete duplicated inputs in test.

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239714273  by Zhichao Lu:

    Adding scope variable to all class heads

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239698643  by Zhichao Lu:

    Create FPN feature extractor for object detection.

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239696657  by Zhichao Lu:

    Internal Change.

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239299404  by Zhichao Lu:

    Allows the faster rcnn meta-architecture to support Keras subcomponents

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238502595  by Zhichao Lu:

    Lay the groundwork for symmetric quantization.

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238496885  by Zhichao Lu:

    Add flexible_grid_anchor_generator

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238138727  by lzc:

    Remove dead code.

    _USE_C_SHAPES has been forced True in TensorFlow releases since
    TensorFlow 1.9
    (https://github.com/tensorflow/tensorflow/commit/1d74a69443f741e69f9f52cb6bc2940b4d4ae3b7)

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238123936  by rathodv:

    Add num_matched_groundtruth summary to target assigner in SSD.

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238103345  by ronnyvotel:

    Raising error if input file pattern does not match any files.
    Also printing the number of evaluation images for coco metrics.

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238044081  by Zhichao Lu:

    Fix docstring to state the correct dimensionality of `class_predictions_with_background`.

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237920279  by Zhichao Lu:

    [XLA] Rework debug flags for dumping HLO.

    The following flags (usually passed via the XLA_FLAGS envvar) are removed:

      xla_dump_computations_to
      xla_dump_executions_to
      xla_dump_ir_to
      xla_dump_optimized_hlo_proto_to
      xla_dump_per_pass_hlo_proto_to
      xla_dump_unoptimized_hlo_proto_to
      xla_generate_hlo_graph
      xla_generate_hlo_text_to
      xla_hlo_dump_as_html
      xla_hlo_graph_path
      xla_log_hlo_text

    The following new flags are added:

      xla_dump_to
      xla_dump_hlo_module_re
      xla_dump_hlo_pass_re
      xla_dump_hlo_as_text
      xla_dump_hlo_as_proto
      xla_dump_hlo_as_dot
      xla_dump_hlo_as_url
      xla_dump_hlo_as_html
      xla_dump_ir
      xla_dump_hlo_snapshots

    The default is not to dump anything at all, but as soon as some dumping flag is
    specified, we enable the following defaults (most of which can be overridden).

     * dump to stdout (overridden by --xla_dump_to)
     * dump HLO modules at the very beginning and end of the optimization pipeline
     * don't dump between any HLO passes (overridden by --xla_dump_hlo_pass_re)
     * dump all HLO modules (overridden by --xla_dump_hlo_module_re)
     * dump in textual format (overridden by
       --xla_dump_hlo_as_{text,proto,dot,url,html}).

    For example, to dump optimized and unoptimized HLO text and protos to /tmp/foo,
    pass

      --xla_dump_to=/tmp/foo --xla_dump_hlo_as_text --xla_dump_hlo_as_proto

    For details on these flags' meanings, see xla.proto.

    The intent of this change is to make dumping both simpler to use and more
    powerful.

    For example:

     * Previously there was no way to dump the HLO module during the pass pipeline
       in HLO text format; the only option was --dump_per_pass_hlo_proto_to, which
       dumped in proto format.

       Now this is --xla_dump_pass_re=.* --xla_dump_hlo_as_text.  (In fact, the
       second flag is not necessary in this case, as dumping as text is the
       default.)

     * Previously there was no way to dump HLO as a graph before and after
       compilation; the only option was --xla_generate_hlo_graph, which would dump
       before/after every pass.

       Now this is --xla_dump_hlo_as_{dot,url,html} (depending on what format you
       want the graph in).

     * Previously, there was no coordination between the filenames written by the
       various flags, so info about one module might be dumped with various
       filename prefixes.  Now the filenames are consistent and all dumps from a
       particular module are next to each other.

    If you only specify some of these flags, we try to figure out what you wanted.
    For example:

     * --xla_dump_to implies --xla_dump_hlo_as_text unless you specify some
       other --xla_dump_as_* flag.

     * --xla_dump_hlo_as_text or --xla_dump_ir implies dumping to stdout unless you
       specify a different --xla_dump_to directory.  You can explicitly dump to
       stdout with --xla_dump_to=-.

    As part of this change, I simplified the debugging code in the HLO passes for
    dumping HLO modules.  Previously, many tests explicitly VLOG'ed the HLO module
    before, after, and sometimes during the pass.  I removed these VLOGs.  If you
    want dumps before/during/after an HLO pass, use --xla_dump_pass_re=<pass_name>.

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237510043  by lzc:

    Internal Change.

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237469515  by Zhichao Lu:

    Parameterize model_builder.build in inputs.py.

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237293511  by rathodv:

    Remove multiclass_scores from tensor_dict in transform_data_fn always.

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237260333  by ronnyvotel:

    Updating faster_rcnn_meta_arch to define prediction dictionary fields that are batched.

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PiperOrigin-RevId: 247226201

196161788  by Zhichao Lu:

    Add eval_on_train_steps parameter.

    Since the number of samples in train dataset is usually different to the number of samples in the eval dataset.

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196151742  by Zhichao Lu:

    Add an optional random sampling process for SSD meta arch and update mean stddev coder to use default std dev when corresponding tensor is not added to boxlist field.

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196148940  by Zhichao Lu:

    Release ssdlite mobilenet v2 coco trained model.

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196058528  by Zhichao Lu:

    Apply FPN feature map generation before we add additional layers on top of resnet feature extractor.

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195818367  by Zhichao Lu:

    Add support for exporting detection keypoints.

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195745420  by Zhichao Lu:

    Introduce include_metrics_per_category option to Object Detection eval_config.

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195734733  by Zhichao Lu:

    Rename SSDLite config to be more explicit.

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195717383  by Zhichao Lu:

    Add quantized training to object_detection.

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195683542  by Zhichao Lu:

    Fix documentation for the interaction of fine_tune_checkpoint_type and load_all_detection_checkpoint_vars interaction.

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195668233  by Zhichao Lu:

    Using batch size from params dictionary if present.

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195570173  by Zhichao Lu:

    A few fixes to get new estimator API eval to match legacy detection eval binary by (1) plumbing `is_crowd` annotations through to COCO evaluator, (2) setting the `sloppy` flag in tf.contrib.data.parallel_interleave based on whether shuffling is enabled, and (3) saving the original image instead of the resized original image, which allows for small/medium/large mAP metrics to be properly computed.

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195316756  by Zhichao Lu:

    Internal change

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PiperOrigin-RevId: 196161788