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Models converted from `saved_model` to `tfjs_graph_model` loose output signature information

See original GitHub issue

Models converted from saved_model to tfjs_graph_model loose output signature information.

This is not specific to any single model, it’s a generic converter issue.

a) Saved model from https://tfhub.dev/tensorflow/efficientdet/d0/1?tf-hub-format=compressed

console.log(await tf.node.getMetaGraphsFromSavedModel(modelPath));

outputs: {
  detection_anchor_indices: { dtype: 'float32', name: 'StatefulPartitionedCall:0', shape: [Array] },
  detection_boxes: { dtype: 'float32', name: 'StatefulPartitionedCall:1', shape: [Array] },
  detection_classes: { dtype: 'float32', name: 'StatefulPartitionedCall:2', shape: [Array] },
  detection_multiclass_scores: { dtype: 'float32', name: 'StatefulPartitionedCall:3', shape: [Array] },
  detection_scores: { dtype: 'float32', name: 'StatefulPartitionedCall:4', shape: [Array] },
  num_detections: { dtype: 'float32', name: 'StatefulPartitionedCall:5', shape: [Array] },
  raw_detection_boxes: { dtype: 'float32', name: 'StatefulPartitionedCall:6', shape: [Array] },
  raw_detection_scores: { dtype: 'float32', name: 'StatefulPartitionedCall:7', shape: [Array] }
}

b) Same model converted to TFJS Graph model using tensorflowjs_converter --input_format=tf_saved_model --output_format=tfjs_graph_model . graph

const model = await tf.loadGraphModel(`file://${path.join(__dirname, modelPath)}`);
console.log(model.executor._signature); // can also use model.outputs, but that has even less info

outputs: {
  'Identity_6:0': { name: 'Identity_6:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '49104' }, { size: '4' }, [length]: 3 ] } },
  'Identity_1:0': { name: 'Identity_1:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '100' }, { size: '4' }, [length]: 3 ] } },
  'Identity_3:0': { name: 'Identity_3:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '100' }, { size: '90' }, [length]: 3 ] } },
  'Identity_2:0': { name: 'Identity_2:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '100' }, [length]: 2 ] } },
  'Identity_5:0': { name: 'Identity_5:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, [length]: 1 ] } },
  'Identity_7:0': { name: 'Identity_7:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '49104' }, { size: '90' }, [length]: 3 ] } },
  'Identity_4:0': { name: 'Identity_4:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '100' }, [length]: 2 ] } },
  'Identity:0': { name: 'Identity:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '100' }, [length]: 2 ] } }
}

This is cosmetic as all outputs are still present, but makes converted models extremely difficult to use.

Environment: Ubuntu 20.04 with NodeJS 14.11.0 and TFJS 2.4.0

Issue Analytics

State:
Created 3 years ago
Reactions:1
Comments:18 (8 by maintainers)

Top GitHub Comments

1reaction

vladmandiccommented, Apr 2, 2021

@rohanmuplara good stuff, but doesn’t help when i’m converting a pretrained model.

0reactions

google-ml-butler[bot]commented, May 7, 2021

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