'Tensorflow 2.0 Object Detection Training Error - Error with loading checkpoint
Object Detection API 2.0, error with load checkpoints: A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used.
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.conv_block.norm.moving_variance
W0716 19:56:53.424076 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.conv_block.norm.moving_variance
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.conv.kernel
W0716 19:56:53.424108 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.conv.kernel
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.axis
W0716 19:56:53.424140 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.axis
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.gamma
W0716 19:56:53.424172 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.gamma
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.beta
W0716 19:56:53.424204 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.beta
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.moving_mean
W0716 19:56:53.424236 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.moving_mean
WARNING:tensorflow:Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.moving_variance
W0716 19:56:53.424268 140587994642240 util.py:144] Unresolved object in checkpoint: (root).model._feature_extractor._network.hourglass_network.1.inner_block.0.inner_block.0.inner_block.0.inner_block.0.decoder_block.1.skip.norm.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 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() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.
W0716 19:56:53.424301 140587994642240 util.py:152] **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 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() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.**
Solution 1:[1]
I was able to get past this error by changing the fine_tune_checkpoint_type to "detection"
I amended the 'pipeline.config' and changed the 'fine_tune_checkpoint_type' from 'classification' to "detection". Thereafter the training happened correctly.
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Subham Tiwari |