I have the following function, which creates a dataset, from two separate dictionaries, by making them a tuple. For example:

```
features = {'input_ids': some.tf.tensor 'input_mask': some.tf.tensor 'segment_ids': some.tf.tensor}
dict2 = {'labels': some.tf.tensor}

support_dataset = tf.data.Dataset.from_tensor_slices((features, dataset["labels"]))

```

what this does is that it casts the concatenation of the two slices as a tuple:

```
support_dataset = ({'input_ids': ..., 'input_mask': ..., 'segment_ids': ...}, {'labels': ...}) 

```

what I want is a single dictionary and not a tuple `{'input_ids': ..., 'input_mask': ..., 'segment_ids': ..., 'labels': ...}` so I can look up the keys by their names. I do not think I can let go of the `tf.data.Dataset.from_tensor_slices((features, dataset["labels"]))` function so is their a way to unpack the tuple while casting it inside the function?