Tensorflow inference with single image with CIFAR-10 example
<p>I'm trying to inference single image using tensorflow cifar10 example:
<a href="https://www.tensorflow.org/versions/r0.8/tutorials/deep_cnn/index.html#convolutional-neural-networks" rel="nofollow">https://www.tensorflow.org/versions/r0.8/tutorials/deep_cnn/index.html#convolutional-neural-networks</a></p>

<blockquote>
<pre><code>def restore_vars(saver, sess):
        """ Restore saved net, global score and step, and epsilons OR
        create checkpoint directory for later storage. """
        #sess.run(tf.initialize_all_variables())

        ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_dir)
        if ckpt and ckpt.model_checkpoint_path:
          # Restores from checkpoint
          saver.restore(sess, ckpt.model_checkpoint_path)
          return True
        else:
          print('No checkpoint file found')
          return False


    def eval_single_img():
        input_img = tf.image.decode_jpeg(tf.read_file("test.jpg"), channels=3)
        input_img = 
        input_img = tf.reshape(input_img, [3, 32, 32])
        input_img = tf.transpose(input_img, [1, 2, 0])
        reshaped_image = tf.cast(input_img, tf.float32)

        resized_image = tf.image.resize_image_with_crop_or_pad(reshaped_image, 24, 24)

        float_image = tf.image.per_image_whitening(resized_image)

        image = tf.expand_dims(float_image, 0)  # create a fake batch of images (batch_size = 1)


        logits = cifar10.inference(image)

        _, top_k_pred = tf.nn.top_k(logits, k=5)

        # Restore the moving average version of the learned variables for eval.
        variable_averages = tf.train.ExponentialMovingAverage(
             cifar10.MOVING_AVERAGE_DECAY)
        variables_to_restore = variable_averages.variables_to_restore()
        saver = tf.train.Saver(variables_to_restore)

        with tf.Session() as sess:
            restored = restore_vars(saver, sess)

            top_indices = sess.run([top_k_pred])
            print ("Predicted ", top_indices[0], " for your input image.")
</code></pre>
</blockquote>

<p>**ERROR MESSAGE:
        tensorflow.python.framework.errors.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [18,384] rhs shape= [2304,384]
                 [[Node: save/Assign_5 = Assign[T=DT_FLOAT, _class=["loc:@local3/weights"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/cpu:0"](local3/weights, save/restore_slice_5)]]
        Caused by op u'save/Assign_5', defined at:</p>

<pre><code>    What might be causing this?**
</code></pre>