Reading data

Reading data

There are three main methods of getting data into a TensorFlow program:

• Feeding: Python code provides the data when running each step.
• Reading from files: an input pipeline reads the data from files at the beginning of a TensorFlow graph.
• Preloaded data: a constant or variable in the TensorFlow graph holds all the data (for small data sets).

Feeding

TensorFlow's feed mechanism lets you inject data into any Tensor in a computation graph. A python computation can thus feed data directly into the graph.

Supply feed data through the feed_dict argument to a run() or eval() call that initiates computation.

with tf.Session():
  input = tf.placeholder(tf.float32)
  classifier = ...
  print(classifier.eval(feed_dict={input: my_python_preprocessing_fn()}))

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