title: Keras fit_generator(datagen.flow(X_train)) function takes less pictures than X_train have?
body: <p>I am using keras <code>fit_generator(datagen.flow())</code> function for training of my inception model, I am so confused about the number of images it is taking on every epoch. Can anyone please help me telling this How it is working. My code is below.</p>
  
  <p>I am using <a href="https://keras.io/preprocessing/image/" rel="nofollow noreferrer">this</a> keras documentation.</p>
  
  <pre class="lang-py prettyprint-override"><code>from keras.preprocessing.image import ImageDataGenerator
  datagen = ImageDataGenerator(rotation_range = 15, horizontal_flip = True)
  
  # Fitting the model with
  history = inc_model.fit_generator(datagen.flow(X_train, train_labels, batch_size=10), epochs=20, validation_data = (X_test, test_labels), callbacks=None)
  </code></pre>
  
  <p>Now my total images in <code>X_train</code> is 4676. However, everytime I run this history line, I get</p>
  
  <pre class="lang-py prettyprint-override"><code>Epoch 1/20
  936/936 [========================] - 167s 179ms/step - loss: 1.4236 - acc: 0.3853 - val_loss: 1.0858 - val_acc: 0.5641
  </code></pre>
  
  <p>Why is it not taking whole of my <code>X_train</code> images? 
  Also, if I change <code>batch_size</code> from 10 to lets say 15 it start taking more less images such as </p>
  
  <pre class="lang-py prettyprint-override"><code>Epoch 1/20 
  436/436
  </code></pre>
  
  <p>Thank you.</p>