Answers.Body: <p>A max-pooling layer doesn't have any trainable weights. It has only hyperparameters, but they are non-trainable. The max-pooling process calculates the maximum value of the filter, which consists of no weights and biases. It is purely a way to downscale the data to a smaller dimension.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-10-28T10:13:21.247Z
Answers.LastActivityDate: 2021-12-31T18:23:34.477Z
Answers.LastEditDate: 2021-12-31T18:23:34.477Z
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Body: <p>How many weights does the max-pooling layer have?</p>
  <p>For example, if there are 10 inputs, a pooling filter of size 2, stride 2, how many weights, including bias, does a max-pooling layer have?</p>
  
Tags: <convolutional-neural-networks><hyper-parameters><filters><pooling><max-pooling>
Title: How many weights does the max-pooling layer have?
UserDisplayName: Tibby
ThreadText: # How many weights does the max-pooling layer have?
  
  (Asked by: username_0 on 2019-10-27)
  
  How many weights does the max-pooling layer have?
  
  For example, if there are 10 inputs, a pooling filter of size 2, stride 2, how many weights, including bias, does a max-pooling layer have?
  
  **Tags:** convolutional-neural-networks, hyper-parameters, filters, pooling, max-pooling
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-10-28. Score: 2 | Accepted answer
  
  A max-pooling layer doesn't have any trainable weights. It has only hyperparameters, but they are non-trainable. The max-pooling process calculates the maximum value of the filter, which consists of no weights and biases. It is purely a way to downscale the data to a smaller dimension.
  
  
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