title: I was trying to implement a object detection on a custom dataset using tensorflow
body: <p>I am new to tensorflow and I was following this [link]<a href="https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html" rel="nofollow noreferrer">https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html</a></p>
  <p>I ran the
  <code>python model_main_tf2.py --model_dir=models/my_ssd_resnet50_v1_fpn --pipeline_config_path=models/my_ssd_resnet50_v1_fpn/pipeline.config</code></p>
  <p>and I was getting a error like this and the program stopped.</p>
  <p>WARNING:tensorflow:A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issue
  s. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check expli
  cit. See <a href="https://www.tensorflow.org/guide/checkpoint#loading_mechanics" rel="nofollow noreferrer">https://www.tensorflow.org/guide/checkpoint#loading_mechanics</a> for details.</p>
  <p>Here are some errors</p>
  <pre><code>W0817 10:14:35.677110 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.0.1.moving_variance
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.0.kernel
  W0817 10:14:35.682097 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.0.kernel
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.axis
  W0817 10:14:35.682097 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.axis
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.gamma
  W0817 10:14:35.683094 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.gamma
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.beta
  W0817 10:14:35.683094 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.beta
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.moving_mean
  W0817 10:14:35.683094 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.moving_mean
  WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.moving_variance
  W0817 10:14:35.684094 16272 util.py:150] Unresolved object in checkpoint: (root).model._feature_extractor._fpn_features_generator.conv_layers.1.1.moving_variance
  WARNING:tensorflow:A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issue
  s. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check expli
  cit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.
  W0817 10:14:35.684094 16272 util.py:158] A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See ab
  ove for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() t
  o make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.
  </code></pre>
  <p>some background:
  I am using windows 10
  I installed tensorflow gpu
  I am using tenforflow 2.3.0</p>