tensorflow / tensorflow/recommenders
DCN notebook example deosn't run the full movielens section
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- Python
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Description
This notebook doesn't fully run when running it in Google Colab (and it should run there with no issues).
Toy example works but Movielens example generates below error:
""""
/usr/local/lib/python3.11/dist-packages/keras/src/layers/layer.py:393: UserWarning: build() was called on layer 'dcn_1', however the layer does not have a build() method implemented and it looks like it has unbuilt state. This will cause the layer to be marked as built, despite not being actually built, which may cause failures down the line. Make sure to implement a proper build() method.
warnings.warn(
ValueError Traceback (most recent call last)
in <cell line: 0>()
----> 1 dcn_result = run_models(use_cross_layer=True,
2 deep_layer_sizes=[192, 192])
2 frames
/usr/local/lib/python3.11/dist-packages/keras/src/backend/tensorflow/trainer.py in multi_step_on_iterator(iterator)
130 if self.steps_per_execution == 1:
131 return tf.experimental.Optional.from_value(
--> 132 one_step_on_data(iterator.get_next())
133 )
134
ValueError: TensorFlowTrainer._make_function..one_step_on_data(data) should not modify its Python input arguments. Modifying a copy is allowed. The following parameter(s) were modified: data
""""
I tried to resolve it and it didn't work, I asked Gemini and that didn't help me to solve the issue either.
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- Open a pull request that references the issue number.
Research direction
Run the DCN notebook's Movielens section in Google Colab, starting with the run_models(use_cross_layer=True, deep_layer_sizes=[192, 192]) call. Investigate the reported TensorFlowTrainer input-modification error and confirm that the full Movielens example completes without the failure.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100