Placeholders allow you to feed values into a tensorflow graph. Aditionally They allow you to specify constraints regarding the dimensions and data type of the values being fed in. As such they are useful when creating a neural network to feed new training examples.
The following example declares a ...
Often one wants to intermittently run one or more validation batches during the course of training a deep network. Typically the training data are fed by a queue while the validation data might be passed through the feed_dict parameter in sess.run(). tf.placeholder_with_default() is designed to work...
