title: Keras input shape error
body: <p>I'm new to Keras and I am trying to create my network which needs to learn on a card game. It takes 93 binary inputs with a hidden layer with 40 neurons and a single output neuron which computes a score (from 0 to 25).</p>
  
  <pre><code>model = Sequential()
  model.add(Dense(input_dim=93, units=40, activation="sigmoid"))
  model.add(Dense(units=2, activation="linear"))
  sgd = optimizers.SGD(lr=0.01, clipvalue=0.5)
  model.compile(loss="mse", optimizer=sgd, learning_rate=0.01)
  </code></pre>
  
  <p>I'm trying first to compute (do a forward propagation) of the 93 inputs</p>
  
  <p>this is "s.toInputs()"</p>
  
  <blockquote>
    <p>[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1
     1 1 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 0 0 1 0 1 0 0 0
     0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 1 1 0 1]</p>
  </blockquote>
  
  <pre><code>model.predict(np.array(s.toInputs())
  </code></pre>
  
  <p>but i get the error </p>
  
  <blockquote>
    <p>ValueError: Error when checking : expected dense_1_input to have shape (None, 93) but got array with shape (93, 1)</p>
  </blockquote>
  
  <p>How do I pass the correct parameters?</p>