function evaluateDataset$1(_x, _x2) {
	      return _evaluateDataset2.apply(this, arguments);
	    }
Evaluate model using a dataset object.

Note: Unlike `evaluate()`, this method is asynchronous (`async`);

@param dataset A dataset object. Its `iterator()` method is expected
  to generate a dataset iterator object, the `next()` method of which
  is expected to produce data batches for evaluation. The return value
  of the `next()` call ought to contain a boolean `done` field and a
  `value` field. The `value` field is expected to be an array of two
  `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
  case is for models with exactly one input and one output (e.g..
  a sequential model). The latter case is for models with multiple
  inputs and/or multiple outputs. Of the two items in the array, the
  first is the input feature(s) and the second is the output target(s).
@param args A configuration object for the dataset-based evaluation.
@returns Loss and metric values as an Array of `Scalar` objects.

@doc {heading: 'Models', subheading: 'Classes'}