Internal change

PiperOrigin-RevId: 386275876

official/vision/beta/MODEL_GARDEN.md

@@ -75,6 +75,7 @@ ResNet-RS-350 | 320x320    | 164.3   | 84.2  | 96.9  | [config](https://github.c
 
 backbone     | resolution | epochs | FLOPs (B) | params (M) | box AP | download
 ------------ | :--------: | -----: | --------: | ---------: | -----: | -------:
+MobileNetv2 | 256x256    | 600    | -       | 2.27       | 23.5   | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/retinanet/coco_mobilenetv2_tpu.yaml) |
 Mobile SpineNet-49  | 384x384    | 600    | 1.0      | 2.32       | 28.1   | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/retinanet/coco_spinenet49_mobile_tpu.yaml) |
 
 

official/vision/beta/configs/experiments/retinanet/coco_mobilenetv2_tpu.yaml

+# --experiment_type=retinanet_mobile_coco
+# COCO AP 23.5%
+runtime:
+  distribution_strategy: 'tpu'
+  mixed_precision_dtype: 'bfloat16'
+task:
+  losses:
+    l2_weight_decay: 3.0e-05
+  model:
+    anchor:
+      anchor_size: 3
+      aspect_ratios: [0.5, 1.0, 2.0]
+      num_scales: 3
+    backbone:
+      mobilenet:
+        model_id: 'MobileNetV2'
+        filter_size_scale: 1.0
+      type: 'mobilenet'
+    decoder:
+      type: 'fpn'
+      fpn:
+        num_filters: 128
+        use_separable_conv: true
+    head:
+      num_convs: 4
+      num_filters: 128
+      use_separable_conv: true
+    input_size: [256, 256, 3]
+    max_level: 7
+    min_level: 3
+    norm_activation:
+      activation: 'relu6'
+      norm_epsilon: 0.001
+      norm_momentum: 0.99
+      use_sync_bn: true
+  train_data:
+    dtype: 'bfloat16'
+    global_batch_size: 256
+    is_training: true
+    parser:
+      aug_rand_hflip: true
+      aug_scale_max: 2.0
+      aug_scale_min: 0.5
+  validation_data:
+    dtype: 'bfloat16'
+    global_batch_size: 8
+    is_training: false
+trainer:
+  optimizer_config:
+    learning_rate:
+      stepwise:
+        boundaries: [263340, 272580]
+        values: [0.32, 0.032, 0.0032]
+      type: 'stepwise'
+    warmup:
+      linear:
+        warmup_learning_rate: 0.0067
+        warmup_steps: 2000
+  steps_per_loop: 462
+  train_steps: 277200
+  validation_interval: 462
+  validation_steps: 625

official/vision/beta/configs/experiments/retinanet/coco_spinenet49_mobile_tpu.yaml

-# --experiment_type=retinanet_spinenet_mobile_coco
+# --experiment_type=retinanet_mobile_coco
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'
@@ -47,7 +47,7 @@ trainer:
   optimizer_config:
     learning_rate:
       stepwise:
-        boundaries: [265650, 272580]
+        boundaries: [263340, 272580]
         values: [0.32, 0.032, 0.0032]
       type: 'stepwise'
     warmup:

official/vision/beta/configs/experiments/retinanet/coco_spinenet49s_mobile_tpu.yaml

-# --experiment_type=retinanet_spinenet_mobile_coco
+# --experiment_type=retinanet_mobile_coco
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'
@@ -47,7 +47,7 @@ trainer:
   optimizer_config:
     learning_rate:
       stepwise:
-        boundaries: [265650, 272580]
+        boundaries: [263340, 272580]
         values: [0.32, 0.032, 0.0032]
       type: 'stepwise'
     warmup:

official/vision/beta/configs/experiments/retinanet/coco_spinenet49xs_mobile_tpu.yaml

-# --experiment_type=retinanet_spinenet_mobile_coco
+# --experiment_type=retinanet_mobile_coco
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'
@@ -47,7 +47,7 @@ trainer:
   optimizer_config:
     learning_rate:
       stepwise:
-        boundaries: [265650, 272580]
+        boundaries: [263340, 272580]
         values: [0.32, 0.032, 0.0032]
       type: 'stepwise'
     warmup:

official/vision/beta/configs/retinanet.py

@@ -326,9 +326,9 @@ def retinanet_spinenet_coco() -> cfg.ExperimentConfig:
   return config
 
 
-@exp_factory.register_config_factory('retinanet_spinenet_mobile_coco')
+@exp_factory.register_config_factory('retinanet_mobile_coco')
 def retinanet_spinenet_mobile_coco() -> cfg.ExperimentConfig:
-  """COCO object detection with RetinaNet using Mobile SpineNet backbone."""
+  """COCO object detection with mobile RetinaNet."""
   train_batch_size = 256
   eval_batch_size = 8
   steps_per_epoch = COCO_TRAIN_EXAMPLES // train_batch_size
@@ -407,8 +407,6 @@ def retinanet_spinenet_mobile_coco() -> cfg.ExperimentConfig:
       restrictions=[
           'task.train_data.is_training != None',
           'task.validation_data.is_training != None',
-          'task.model.min_level == task.model.backbone.spinenet_mobile.min_level',
-          'task.model.max_level == task.model.backbone.spinenet_mobile.max_level',
       ])
 
   return config

official/vision/beta/configs/retinanet_test.py

@@ -28,7 +28,7 @@ class RetinaNetConfigTest(tf.test.TestCase, parameterized.TestCase):
   @parameterized.parameters(
       ('retinanet_resnetfpn_coco',),
       ('retinanet_spinenet_coco',),
-      ('retinanet_spinenet_mobile_coco',),
+      ('retinanet_mobile_coco',),
   )
   def test_retinanet_configs(self, config_name):
     config = exp_factory.get_exp_config(config_name)