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Build a supervised_input_receiver_fn for raw features and labels.
tf.estimator.experimental.build_raw_supervised_input_receiver_fn( features, labels, default_batch_size=None )
This function wraps tensor placeholders in a supervised_receiver_fn with the expectation that the features and labels appear precisely as the model_fn expects them. Features and labels can therefore be dicts of tensors, or raw tensors.
features: a dict of string to
labels: a dict of string to
default_batch_size: the number of query examples expected per batch. Leave unset for variable batch size (recommended).
ValueError: if features and labels have overlapping keys.