title: output label Y train shape keras tensorflow 1.4
body: <p>I am running VGG16 network for image classification on svhn database.
  I am saving images into shape (None,64,64,3) and labels of shape <strong>(None,10)</strong>.Labels are 1d array of size 10.</p>
  
  <p>Below is the part of my code.</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import cv2
  import tensorflow as tf
  import os
  import scipy
  from skimage import data, io, filters
  import scipy.io as sio
  from utils import *
  import h5py
  
  vgg = tf.keras.applications.vgg16.VGG16 (include_top=False,
  weights='imagenet',
  input_tensor=None,
  input_shape=(64,64,3),
  pooling='avg',
  classes=10)
  
  vgg.compile(loss='categorical_crossentropy',
            optimizer='sgd',
            metrics=['accuracy'])
  
  vgg.fit(train_data, labels_data, epochs=5, batch_size=32)
  </code></pre>
  
  <p>and so I get error:</p>
  
  <pre><code>    ValueError: Error when checking target: expected block5_pool to have shape (None, 512) but got array with shape (None, 10)
  </code></pre>
  
  <p>What changes should I do? </p>