added center heatmap and offset losses

official/vision/beta/projects/panoptic_maskrcnn/losses/panoptic_deeplab_losses.py

+# 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.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Instance center losses used for panoptic deeplab model."""
+
+# Import libraries
+import tensorflow as tf
+from official.modeling import tf_utils
+
+
+class CenterLoss:
+  """Instance center loss."""
+  
+  _LOSS_FN = {
+      'mse': tf.losses.mean_squared_error,
+      'mae': tf.losses.mean_absolute_error
+  }
+
+  def __init__(self, use_groundtruth_dimension: bool, loss_type: str):
+    if loss_type.lower() not in {'mse', 'mae'}:
+      raise ValueError('Unsupported `loss_type` supported. Available loss '
+                       'types: mse/mae')
+
+    self._use_groundtruth_dimension = use_groundtruth_dimension
+    self.loss_type = loss_type
+    self._loss_fn = CenterLoss._LOSS_FN[self.loss_type]
+
+  def __call__(self, logits, labels, sample_weight):
+    _, height, width, _ = logits.get_shape().as_list()
+
+    if self._use_groundtruth_dimension:
+      logits = tf.image.resize(
+          logits, tf.shape(labels)[1:3],
+          method=tf.image.ResizeMethod.BILINEAR)
+    else:
+      labels = tf.image.resize(
+          labels, (height, width),
+          method=tf.image.ResizeMethod.BILINEAR)
+
+    loss = self._loss_fn(y_true=labels, y_pred=logits)
+    return tf_utils.safe_mean(loss * sample_weight)
+
+
+class CenterHeatmapLoss(CenterLoss):
+  def __init__(self, use_groundtruth_dimension):
+    super(CenterHeatmapLoss, self).__init__(
+        use_groundtruth_dimension=use_groundtruth_dimension,
+        loss_type='mse')
+
+class CenterOffsetLoss(CenterLoss):
+  def __init__(self, use_groundtruth_dimension):
+    super(CenterOffsetLoss, self).__init__(
+        use_groundtruth_dimension=use_groundtruth_dimension,
+        loss_type='mae')