title: mnist CNN ValueError expected min_ndim=4, found ndim=3. Full shape received: [32, 28, 28]
body: <p>I define the model definition as follows.</p>
  <pre><code>tf.keras.datasets.mnist 
  model = keras.models.Sequential([  
      tf.keras.layers.Conv2D(28, (3,3), activation='relu', input_shape=(28, 28, 1)),  
      tf.keras.layers.MaxPooling2D((2, 2)),  
      tf.keras.layers.Conv2D(56, (3,3), activation='relu'),  
      tf.keras.layers.Flatten(),  
      tf.keras.layers.Dense(64, activation='relu'),  
      tf.keras.layers.Dense(10, activation='softmax'),  
  ])  
  model.fit(x_train, y_train, epochs=3)  &lt;----error
  </code></pre>
  <p>When I try to run with my data set, it gives the following error.</p>
  <pre><code> ValueError: Input 0 of layer sequential_3 is incompatible with the layer: : expected min_ndim=4, found ndim=3. Full shape received: [32, 28, 28]
  </code></pre>