title: Imbalance Learn "balanced_batch_generator" for > 2 dimensional data
body: <p>I am using imbalanced learn's "balanced_batch_generator" to try to perform undersampling on image array which has 4 dimensions. I ran the code below:</p>
  
  <pre><code>training_generator, steps_per_epoch = balanced_batch_generator(x_train, y_train, sampler=NearMiss(), batch_size=10)
  </code></pre>
  
  <p>and got the following error:</p>
  
  <pre><code>ValueError: Found array with dim 4. Estimator expected &lt;= 2.
  </code></pre>
  
  <p>I am aware that this function does not accept > 2 dimensional data however I am wondering if there is an work around to this. I would perform under/over sampling myself by just manually splitting the data, however i want to make use of keras's nicely implemented functions such as <code>NearMiss</code> to intelligently sample my data.</p>