Produce balanced mini batch with Dataset API

Question

I\'ve a question about the new dataset API (tensorflow 1.4rc1). I\'ve a unbalanced dataset wrt to labels 0 and 1. My goal is to create balanced min

Answer 1

You are on the right track. The following example uses Dataset.flat_map() to turn each pair of a positive example and a negative example into two consecutive examples in the result:

dataset = tf.data.Dataset.zip((ds_pos, ds_neg))

# Each input element will be converted into a two-element `Dataset` using
# `Dataset.from_tensors()` and `Dataset.concatenate()`, then `Dataset.flat_map()`
# will flatten the resulting `Dataset`s into a single `Dataset`.
dataset = dataset.flat_map(
    lambda ex_pos, ex_neg: tf.data.Dataset.from_tensors(ex_pos).concatenate(
        tf.data.Dataset.from_tensors(ex_neg)))

dataset = dataset.batch(20)