|TensorFlow 2 version||View source on GitHub|
Representative dataset to evaluate optimizations.
A representative dataset that can be used to evaluate optimizations by the converter. E.g. converter can use these examples to estimate (min, max) ranges by calibrating the model on inputs. This can allow converter to quantize a converted floating point model.
Creates a representative dataset.
input_gen: an input generator that can be used to generate input samples for the model. This must be a callable object that returns an object that supports the
iter()protocol (e.g. a generator function). The elements generated must have same type and shape as inputs to the model.