Update code to v2.11.0

official/legacy/detection/utils/class_utils.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/detection/utils/dataloader_utils.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/detection/utils/input_utils.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/detection/utils/mask_utils.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/README.md

 # Image Classification
 
-**Warning:** the features in the `image_classification/` folder have been fully
-integrated into vision/beta. Please use the [new code base](../../vision/beta/README.md).
+**Warning:** the features in the `image_classification/` directory have been
+fully integrated into the [new code base](https://github.com/tensorflow/models/tree/benchmark/official/vision/modeling/backbones).
 
-This folder contains TF 2.0 model examples for image classification:
+This folder contains TF 2 model examples for image classification:
 
 * [MNIST](#mnist)
 * [Classifier Trainer](#classifier-trainer), a framework that uses the Keras
@@ -17,8 +17,7 @@ For more information about other types of models, please refer to this
 
 ## Before you begin
 Please make sure that you have the latest version of TensorFlow
-installed and
-[add the models folder to your Python path](/official/#running-the-models).
+installed and add the models folder to your Python path.
 
 ### ImageNet preparation
 
@@ -70,6 +69,7 @@ available GPUs at each host.
 To download the data and run the MNIST sample model locally for the first time,
 run one of the following command:
 
+<details>
 ```bash
 python3 mnist_main.py \
   --model_dir=$MODEL_DIR \
@@ -79,9 +79,11 @@ python3 mnist_main.py \
   --num_gpus=$NUM_GPUS \
   --download
 ```
+</details>
 
 To train the model on a Cloud TPU, run the following command:
 
+<details>
 ```bash
 python3 mnist_main.py \
   --tpu=$TPU_NAME \
@@ -91,10 +93,10 @@ python3 mnist_main.py \
   --distribution_strategy=tpu \
   --download
 ```
+</details>
 
 Note: the `--download` flag is only required the first time you run the model.
 
-
 ## Classifier Trainer
 The classifier trainer is a unified framework for running image classification
 models using Keras's compile/fit methods. Experiments should be provided in the
@@ -111,6 +113,8 @@ be 64 * 8 = 512, and for a v3-32, the global batch size is 64 * 32 = 2048.
 ### ResNet50
 
 #### On GPU:
+
+<details>
 ```bash
 python3 classifier_trainer.py \
   --mode=train_and_eval \
@@ -121,12 +125,15 @@ python3 classifier_trainer.py \
   --config_file=configs/examples/resnet/imagenet/gpu.yaml \
   --params_override='runtime.num_gpus=$NUM_GPUS'
 ```
+</details>
 
 To train on multiple hosts, each with GPUs attached using
 [MultiWorkerMirroredStrategy](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/MultiWorkerMirroredStrategy)
 please update `runtime` section in gpu.yaml
 (or override using `--params_override`) with:
 
+<details>
+
 ```YAML
 # gpu.yaml
 runtime:
@@ -135,12 +142,16 @@ runtime:
   num_gpus: $NUM_GPUS
   task_index: 0
 ```
+</details>
+
 By having `task_index: 0` on the first host and `task_index: 1` on the second
 and so on. `$HOST1` and `$HOST2` are the IP addresses of the hosts, and `port`
 can be chosen any free port on the hosts. Only the first host will write
 TensorBoard Summaries and save checkpoints.
 
 #### On TPU:
+
+<details>
 ```bash
 python3 classifier_trainer.py \
   --mode=train_and_eval \
@@ -152,9 +163,31 @@ python3 classifier_trainer.py \
   --config_file=configs/examples/resnet/imagenet/tpu.yaml
 ```
 
+</details>
+
+### VGG-16
+
+#### On GPU:
+
+<details>
+```bash
+python3 classifier_trainer.py \
+  --mode=train_and_eval \
+  --model_type=vgg \
+  --dataset=imagenet \
+  --model_dir=$MODEL_DIR \
+  --data_dir=$DATA_DIR \
+  --config_file=configs/examples/vgg/imagenet/gpu.yaml \
+  --params_override='runtime.num_gpus=$NUM_GPUS'
+```
+
+</details>
+
 ### EfficientNet
 **Note: EfficientNet development is a work in progress.**
 #### On GPU:
+
+<details>
 ```bash
 python3 classifier_trainer.py \
   --mode=train_and_eval \
@@ -166,8 +199,11 @@ python3 classifier_trainer.py \
   --params_override='runtime.num_gpus=$NUM_GPUS'
 ```
 
+</details>
 
 #### On TPU:
+
+<details>
 ```bash
 python3 classifier_trainer.py \
   --mode=train_and_eval \
@@ -178,6 +214,7 @@ python3 classifier_trainer.py \
   --data_dir=$DATA_DIR \
   --config_file=configs/examples/efficientnet/imagenet/efficientnet-b0-tpu.yaml
 ```
+</details>
 
 Note that the number of GPU devices can be overridden in the command line using
 `--params_overrides`. The TPU does not need this override as the device is fixed

official/legacy/image_classification/__init__.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/augment.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/augment_test.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/callbacks.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Common modules for callbacks."""
 from __future__ import absolute_import
 from __future__ import division

official/legacy/image_classification/classifier_trainer.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Runs an Image Classification model."""
 
 import os
@@ -32,6 +31,7 @@ from official.legacy.image_classification.configs import configs
 from official.legacy.image_classification.efficientnet import efficientnet_model
 from official.legacy.image_classification.resnet import common
 from official.legacy.image_classification.resnet import resnet_model
+from official.legacy.image_classification.vgg import vgg_model
 from official.modeling import hyperparams
 from official.modeling import performance
 from official.utils import hyperparams_flags
@@ -43,6 +43,7 @@ def get_models() -> Mapping[str, tf.keras.Model]:
   return {
       'efficientnet': efficientnet_model.EfficientNet.from_name,
       'resnet': resnet_model.resnet50,
+      'vgg': vgg_model.vgg16,
   }
 
 

official/legacy/image_classification/classifier_trainer_test.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,13 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Unit tests for the classifier trainer models."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
 import functools
 import json
 
@@ -53,6 +48,7 @@ def distribution_strategy_combinations() -> Iterable[Tuple[Any, ...]]:
       model=[
           'efficientnet',
           'resnet',
+          'vgg',
       ],
       dataset=[
           'imagenet',
@@ -149,6 +145,7 @@ class ClassifierTest(tf.test.TestCase, parameterized.TestCase):
           model=[
               'efficientnet',
               'resnet',
+              'vgg',
           ],
           dataset='imagenet',
           dtype='float16',
@@ -193,6 +190,7 @@ class ClassifierTest(tf.test.TestCase, parameterized.TestCase):
           model=[
               'efficientnet',
               'resnet',
+              'vgg',
           ],
           dataset='imagenet',
           dtype='bfloat16',

official/legacy/image_classification/classifier_trainer_util_test.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Unit tests for the classifier trainer models."""
 
 from __future__ import absolute_import

official/legacy/image_classification/configs/__init__.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/configs/base_configs.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Definitions for high level configuration groups.."""
 
 import dataclasses

official/legacy/image_classification/configs/configs.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,11 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Configuration utils for image classification experiments."""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import dataclasses
 
@@ -24,6 +20,7 @@ from official.legacy.image_classification import dataset_factory
 from official.legacy.image_classification.configs import base_configs
 from official.legacy.image_classification.efficientnet import efficientnet_config
 from official.legacy.image_classification.resnet import resnet_config
+from official.legacy.image_classification.vgg import vgg_config
 
 
 @dataclasses.dataclass
@@ -92,12 +89,38 @@ class ResNetImagenetConfig(base_configs.ExperimentConfig):
   model: base_configs.ModelConfig = resnet_config.ResNetModelConfig()
 
 
+@dataclasses.dataclass
+class VGGImagenetConfig(base_configs.ExperimentConfig):
+  """Base configuration to train vgg-16 on ImageNet."""
+  export: base_configs.ExportConfig = base_configs.ExportConfig()
+  runtime: base_configs.RuntimeConfig = base_configs.RuntimeConfig()
+  train_dataset: dataset_factory.DatasetConfig = dataset_factory.ImageNetConfig(
+      split='train', one_hot=False, mean_subtract=True, standardize=True)
+  validation_dataset: dataset_factory.DatasetConfig = dataset_factory.ImageNetConfig(
+      split='validation', one_hot=False, mean_subtract=True, standardize=True)
+  train: base_configs.TrainConfig = base_configs.TrainConfig(
+      resume_checkpoint=True,
+      epochs=90,
+      steps=None,
+      callbacks=base_configs.CallbacksConfig(
+          enable_checkpoint_and_export=True, enable_tensorboard=True),
+      metrics=['accuracy', 'top_5'],
+      time_history=base_configs.TimeHistoryConfig(log_steps=100),
+      tensorboard=base_configs.TensorBoardConfig(
+          track_lr=True, write_model_weights=False),
+      set_epoch_loop=False)
+  evaluation: base_configs.EvalConfig = base_configs.EvalConfig(
+      epochs_between_evals=1, steps=None)
+  model: base_configs.ModelConfig = vgg_config.VGGModelConfig()
+
+
 def get_config(model: str, dataset: str) -> base_configs.ExperimentConfig:
   """Given model and dataset names, return the ExperimentConfig."""
   dataset_model_config_map = {
       'imagenet': {
           'efficientnet': EfficientNetImageNetConfig(),
           'resnet': ResNetImagenetConfig(),
+          'vgg': VGGImagenetConfig(),
       }
   }
   try:

official/legacy/image_classification/configs/examples/vgg16/imagenet/gpu.yaml

+# Training configuration for VGG-16 trained on ImageNet on GPUs.
+# Reaches > 72.8% within 90 epochs.
+# Note: This configuration uses a scaled per-replica batch size based on the number of devices.
+runtime:
+  distribution_strategy: 'mirrored'
+  num_gpus: 1
+  batchnorm_spatial_persistent: true
+train_dataset:
+  name: 'imagenet2012'
+  data_dir: null
+  builder: 'records'
+  split: 'train'
+  image_size: 224
+  num_classes: 1000
+  num_examples: 1281167
+  batch_size: 128
+  use_per_replica_batch_size: true
+  dtype: 'float32'
+  mean_subtract: true
+  standardize: true
+validation_dataset:
+  name: 'imagenet2012'
+  data_dir: null
+  builder: 'records'
+  split: 'validation'
+  image_size: 224
+  num_classes: 1000
+  num_examples: 50000
+  batch_size: 128
+  use_per_replica_batch_size: true
+  dtype: 'float32'
+  mean_subtract: true
+  standardize: true
+model:
+  name: 'vgg'
+  optimizer:
+    name: 'momentum'
+    momentum: 0.9
+    epsilon: 0.001
+  loss:
+    label_smoothing: 0.0
+train:
+  resume_checkpoint: true
+  epochs: 90
+evaluation:
+  epochs_between_evals: 1

official/legacy/image_classification/dataset_factory.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Dataset utilities for vision tasks using TFDS and tf.data.Dataset."""
 from __future__ import absolute_import
 from __future__ import division

official/legacy/image_classification/efficientnet/__init__.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/efficientnet/common_modules.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/legacy/image_classification/efficientnet/efficientnet_config.py

-# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Lint as: python3
 """Configuration definitions for EfficientNet losses, learning rates, and optimizers."""
 from __future__ import absolute_import
 from __future__ import division