title: How does model.evaluate() work in tensorflow?
body: <p>I'm training a model with a 4 day look back and 4 days future forecast. The last 4 days will be acting as a feature for the next days.</p>
  <p>In that case if i have x_test as <code>[[1,2,3,4],[5,6,7,8]]</code> and <code>y_test[[0.1,0.2,0.3,0.4],[0.5,0.6,0.7,0.8]]</code></p>
  <p>if we do a <code>model.predict(x_test[0])</code>, the result <code>y(hat)</code> we need to comapare with <code>y[1].</code></p>
  <p>So how is <code>model.evaluate()</code> doing this comparison? if we comapre <code>y(hat)[0]</code> with <code>y[0]</code>, it is wrong right?</p>