title: Creating a Y_true Dataset in Keras
body: <p>Here's my current call to model.fit in Keras </p>
  
  <pre><code>history_callback = model.fit(x_train/255.,
                               validation_train_data,
                               validation_split=validation_split,
                               batch_size=batch_size,
                               callbacks=callbacks)
  </code></pre>
  
  <p>in this example <code>x_train</code> is a list of numpy arrays that contains all of my image data. The way <code>validation_train_data</code> is structured though is its a list of numpy arrays of totally different sizes that is equal in length to the list of numpy arrays that contains my image. The data for each image though is contained in validation_train_data such that <code>x_train[i]</code> would correspond to a set containing <code>validation_train_data[0][i]</code>, <code>validation_train_data[1][i]</code>, <code>validation_train_data[2][i]</code>, etc. Is there any way I can reformat my validation_train_data such that it can properly be used as a <code>y_true</code> in a custom keras loss function.</p>