TensorFlow code structure
The TensorFlow programming model signifies how to structure your predictive models. A TensorFlow program is generally divided into four phases when you have imported the TensorFlow library:
- Construction of the computational graph that involves some operations on tensors (we will see what a tensor is soon)
- Creation of a session
- Running a session; performed for the operations defined in the graph
- Computation for data collection and analysis
These main phases define the programming model in TensorFlow. Consider the following example, in which we want to multiply two numbers:
import tensorflow as tf # Import TensorFlow x = tf.constant(8) # X op y = tf.constant(9) # Y op z = tf.multiply(x, y) # New op Z sess = tf.Session() # Create ...
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