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Editor to share with you the example analysis of the TensorFlow neural network in Python, I believe that most people do not know much about it, so share this article for your reference, I hope you can learn a lot after reading this article, let's go to know it!

1. Basic theory 1. TensorFlow

Tensor: tensor (data)

Flow: flow

Tensor-Flow: data flow

2. TensorFlow process

TensorFlow composition: figure and session

1. Construction diagram phase

Construction phase: data (tensor tensor) and operation (node operation) are defined to form a diagram (static).

Tensor: the basic data object in TensorFlow.

Node: provides the actions performed in the figure.

2. Execute the diagram phase (session)

Execution phase: use the session to perform defined data and operations.

2. TensorFlow instance (perform addition) 1, construct static figure 1-1, create data (tensor) # figure (static) a = tf.constant (2) # data 1 (tensor) b = tf.constant (6) # data 2 (tensor) 1-2, create operation (node) c = a + b # operation (node) 2, session (execution) API:

Normal execution # session (execution) with tf.Session () as sess: print (sess.run (a + b))

Fetches (multi-parameter execution) # session (execution) with tf.Session () as sess: print (sess.run ([amembpenc]))

Feed_dict (parameter supplement) def Feed_Add (): # create a static graph a = tf.placeholder (tf.float32) b = tf.placeholder (tf.float32) c = tf.add (Azov b) # session (execution) with tf.Session () as sess: print (c, feed_dict= {aVO0.5, bGV 2.0}))

Total code import tensorflow as tfdef Add (): # figure (static) a = tf.constant (2) # data 1 (tensor) b = tf.constant (6) # data 2 (tensor) c = a + b # operation (node) # session (execution) with tf.Session () as sess: sess.run ([Azob C])) def Feed_Add (): # create a static graph a = tf.placeholder (tf.float32) b = tf.placeholder (tf.float32) c = tf.add (Azov b) # session (execution) with tf.Session () as sess: print (sess.run (c, feed_dict= {avel0.5) Add () Feed_Add () above are all the contents of the article "example Analysis of TensorFlow Neural Networks in Python" Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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