How do I fix TensorFlow/Keras error : "ValueError: Value returned by __array__ is not a NumPy array"

Question

I'm following the ML course "Create and implement machine learning models" - Create machine learning models

Section - Train and evaluate deep learning models

Unit 3 - Exercise - Train a deep neural network, under sub section "Train a deep neural network model"

Using the notebook: 05a - Deep Neural Networks (TensorFlow).ipynb

Section "Train the model"

initially I had the following error which I fixed:

opt = optimizers.Adam(lr=learning_rate) --> ValueError: Argument(s) not recognized: {'lr': 0.001}

changed to --> opt = optimizers.Adam(learning_rate)

now getting the error "ValueError: Value returned by array is not a NumPy array". I've not changed the data sample and using the core code that was downloaded from github as per instruction in the course.

I've inspected all the variables going used to call the fit function (x_train, y_train, x_test, y_test) and they see me to be correct data type.

Below is the stack trace :

---

ValueError Traceback (most recent call last)

Cell In[9], line 11

  9 # Train the model over 50 epochs using 10-observation batches and using the test holdout dataset for validation

 10 num_epochs = 50

---> 11 history = model.fit(x_train, y_train, epochs=num_epochs, batch_size=10, validation_data=(x_test, y_test))

File /anaconda/envs/azureml_py38/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py:122, in filter_traceback.<locals>.error_handler(*args, **kwargs)

119     filtered_tb = _process_traceback_frames(e.__traceback__)

120     # To get the full stack trace, call:

121     # `keras.config.disable_traceback_filtering()`

--> 122 raise e.with_traceback(filtered_tb) from None

123 finally:

124     del filtered_tb

File /anaconda/envs/azureml_py38/lib/python3.10/site-packages/tensorflow/python/framework/constant_op.py:108, in convert_to_eager_tensor(value, ctx, dtype)

106     dtype = dtypes.as_dtype(dtype).as_datatype_enum

107 ctx.ensure_initialized()

--> 108 return ops.EagerTensor(value, ctx.device_name, dtype)

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