Update code to v2.11.0

official/projects/backbone_reuse/configs/experiments/faster_rcnn/fastrcnn_resnet101_fpn_cascade_72epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: fpn
+    detection_head:
+      cascade_class_ensemble: true
+      class_agnostic_bbox_pred: true
+      num_fcs: 2
+    input_size: [1280, 1280, 3]
+    norm_activation:
+      activation: swish
+    roi_sampler:
+      cascade_iou_thresholds: [0.7, 0.8]
+  train_data:
+    global_batch_size: 64
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [88704, 125664]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.16, 0.016, 0.0016]
+      type: stepwise
+  steps_per_loop: 1848
+  summary_interval: 1848
+  train_steps: 133056

official/projects/backbone_reuse/configs/experiments/faster_rcnn/fastrcnn_resnet101_nasfpn_600epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+    detection_head:
+      num_fcs: 2
+    include_mask: false
+    max_level: 7
+    min_level: 3
+    norm_activation:
+      activation: swish
+  train_data:
+    global_batch_size: 64
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [1062734, 1090458]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.16, 0.016, 0.0016]
+      type: stepwise
+  steps_per_loop: 1848
+  summary_interval: 1848
+  train_steps: 1108940

official/projects/backbone_reuse/configs/experiments/faster_rcnn/fastrcnn_resnet101_nasfpn_72epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+    detection_head:
+      num_fcs: 2
+    include_mask: false
+    max_level: 7
+    min_level: 3
+    norm_activation:
+      activation: swish
+  train_data:
+    global_batch_size: 64
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [88704, 125664]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.16, 0.016, 0.0016]
+      type: stepwise
+  steps_per_loop: 1848
+  summary_interval: 1848
+  train_steps: 133056

official/projects/backbone_reuse/configs/experiments/faster_rcnn/fastrcnn_resnet101_nasfpn_cascade_600epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+    detection_head:
+      cascade_class_ensemble: true
+      class_agnostic_bbox_pred: true
+      num_fcs: 2
+    input_size: [1280, 1280, 3]
+    max_level: 7
+    min_level: 3
+    norm_activation:
+      activation: swish
+    roi_sampler:
+      cascade_iou_thresholds: [0.7, 0.8]
+  train_data:
+    global_batch_size: 64
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [1062734, 1090458]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.16, 0.016, 0.0016]
+      type: stepwise
+  steps_per_loop: 1848
+  summary_interval: 1848
+  train_steps: 1108940

official/projects/backbone_reuse/configs/experiments/faster_rcnn/fastrcnn_resnet101_nasfpn_cascade_72epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+    detection_head:
+      cascade_class_ensemble: true
+      class_agnostic_bbox_pred: true
+      num_fcs: 2
+    input_size: [1280, 1280, 3]
+    max_level: 7
+    min_level: 3
+    norm_activation:
+      activation: swish
+    roi_sampler:
+      cascade_iou_thresholds: [0.7, 0.8]
+  train_data:
+    global_batch_size: 64
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [88704, 125664]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.16, 0.016, 0.0016]
+      type: stepwise
+  steps_per_loop: 1848
+  summary_interval: 1848
+  train_steps: 133056

official/projects/backbone_reuse/configs/experiments/retinanet/retinanet_resnet101_fpn_600epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: fpn
+  train_data:
+    global_batch_size: 256
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [265684, 272615]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.32, 0.032, 0.0032]
+      type: stepwise
+  steps_per_loop: 462
+  summary_interval: 462
+  train_steps: 277235

official/projects/backbone_reuse/configs/experiments/retinanet/retinanet_resnet101_fpn_72epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: fpn
+  train_data:
+    global_batch_size: 256
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [22176, 31416]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.32, 0.032, 0.0032]
+      type: stepwise
+  steps_per_loop: 462
+  summary_interval: 462
+  train_steps: 33264

official/projects/backbone_reuse/configs/experiments/retinanet/retinanet_resnet101_nasfpn_600epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+  train_data:
+    global_batch_size: 256
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [265684, 272615]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.32, 0.032, 0.0032]
+      type: stepwise
+  steps_per_loop: 462
+  summary_interval: 462
+  train_steps: 277235

official/projects/backbone_reuse/configs/experiments/retinanet/retinanet_resnet101_nasfpn_72epochs.yaml

+task:
+  # init_checkpoint: 'a_pretrained_backbone_checkpoint'
+  init_checkpoint_modules: backbone
+  freeze_backbone: true
+  model:
+    backbone:
+      resnet:
+        model_id: 101
+        replace_stem_max_pool: true
+        resnetd_shortcut: true
+        scale_stem: true
+        se_ratio: 0.25
+        stem_type: v1
+      type: resnet
+    decoder:
+      type: nasfpn
+  train_data:
+    global_batch_size: 256
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.1
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [22176, 31416]
+        name: PiecewiseConstantDecay
+        offset: 0
+        values: [0.32, 0.032, 0.0032]
+      type: stepwise
+  steps_per_loop: 462
+  summary_interval: 462
+  train_steps: 33264

official/projects/basnet/configs/basnet.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.
@@ -20,7 +20,7 @@ from official.core import config_definitions as cfg
 from official.core import exp_factory
 from official.modeling import hyperparams
 from official.modeling import optimization
-from official.vision.beta.configs import common
+from official.vision.configs import common
 
 
 @dataclasses.dataclass

official/projects/basnet/configs/basnet_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/projects/basnet/evaluation/metrics.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/projects/basnet/evaluation/metrics_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/projects/basnet/losses/basnet_losses.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/projects/basnet/modeling/basnet_model.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.
@@ -20,7 +20,7 @@ import tensorflow as tf
 
 from official.modeling import tf_utils
 from official.projects.basnet.modeling import nn_blocks
-from official.vision.beta.modeling.backbones import factory
+from official.vision.modeling.backbones import factory
 
 # Specifications for BASNet encoder.
 # Each element in the block configuration is in the following format:

official/projects/basnet/modeling/basnet_model_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/projects/basnet/modeling/nn_blocks.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/projects/basnet/modeling/refunet.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/projects/basnet/serving/basnet.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.
@@ -17,11 +17,7 @@
 import tensorflow as tf
 
 from official.projects.basnet.tasks import basnet
-from official.vision.beta.serving import semantic_segmentation
-
-
-MEAN_RGB = (0.485 * 255, 0.456 * 255, 0.406 * 255)
-STDDEV_RGB = (0.229 * 255, 0.224 * 255, 0.225 * 255)
+from official.vision.serving import semantic_segmentation
 
 
 class BASNetModule(semantic_segmentation.SegmentationModule):

official/projects/basnet/serving/export_saved_model.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.
@@ -41,7 +41,7 @@ from absl import flags
 from official.core import exp_factory
 from official.modeling import hyperparams
 from official.projects.basnet.serving import basnet
-from official.vision.beta.serving import export_saved_model_lib
+from official.vision.serving import export_saved_model_lib
 
 FLAGS = flags.FLAGS