ValueError when calling model.predict_step

[cam]

When using the "sharing model" feature, the tool produces code to copy and execute in a new Google Colab notebook. Here is the snippet to predict a step

# Make predictions with the model

examples = {
  "value" : ["<OOD>, second, fourth, third, fifth, first", "<OOD>, third, fifth, first, fourth, second, sixth."],
}
model.predict_step(examples)

This code does not work out of the box and generates the following error:

ValueError: Exception encountered when calling layer 'inference_core_model_4' (type InferenceCoreModel).

Could not find matching concrete function to call loaded from the SavedModel. Got:
  Positional arguments (2 total):
    * {'value': ['<OOD>, second, fourth, third, fifth, first',
           '<OOD>, third, fifth, first, fourth, second, sixth.']}
    * False
  Keyword arguments: {}

 Expected these arguments to match one of the following 2 option(s):

Option 1:
  Positional arguments (2 total):
    * {'value': RaggedTensorSpec(TensorShape([None, None]), tf.string, 1, tf.int64)}
    * False
  Keyword arguments: {}

Option 2:
  Positional arguments (2 total):
    * {'value': RaggedTensorSpec(TensorShape([None, None]), tf.string, 1, tf.int64)}
    * True
  Keyword arguments: {}

Call arguments received by layer 'inference_core_model_4' (type InferenceCoreModel):
  • args=({'value': ["'<OOD>, second, fourth, third, fifth, first'", "'<OOD>, third, fifth, first, fourth, second, sixth.'"]},)
  • kwargs={'training': 'False'}

Can the example code produced by the SimpleML tool be modified to something that works without modification?

How can I modify the examples variable so the call succeeds? 

[Carlos Sutrun]

+1, I have got the same error. 

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[Luiz Gustavo Martins]

Hi,

We are looking into that issue and we will get back to you as soon as we have a fix.

sorry

   Gus

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