How to give a list of integers as input in Tensorflow Dataset?

Question

We are trying to finetune/train a pretrained RoBERTa model using tensorflow. For this we have to create a tf.data.Dataset from our dataframe.

The dataframe looks like this:

Where the three options are encoded strings, and the answer is an integer which corresponds to option A, B or C.

We try to make a tf.dataset from this using:

features= ['OptionA', 'OptionB', 'OptionC']

training_dataset = (
    tf.data.Dataset.from_tensor_slices(
        (
            tf.cast(train_data[features].values, tf.float32),
            tf.cast(train_data['Answer'].values, tf.int32)
        )
    )
)

However this does not work as we get the following error:

ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type list).

I have read that we can not use lists as an tf.dtype, where we have put 'float32' now. But we also cannot convert the lists in the dataframe to floats.

How can we resolve this?

Answer 1

features = np.asarray(features).astype('float32')

Should work.

Tensorflow - ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float)

^the top solution in this has a more in-depth answer.