Inputs, variables, outputs, and operations
Now with an understanding of the underlying architecture let's proceed to the most common elements that comprise a TensorFlow client. If you read any of the millions of TensorFlow clients available on the internet, they all (the TensorFlow-related code) fall into one of these buckets:
- Inputs: Data used to train and test our algorithms
- Variables: Mutable tensors, mostly defining the parameters of our algorithms
- Outputs: Immutable tensors storing both terminal and intermediate outputs
- Operations: Various transformations for inputs to produce the desired outputs
In our earlier example, in the sigmoid example, we can find instances of all these categories. We list the elements in Table 2.1:
|
TensorFlow element ... |
|---|
Get Natural Language Processing with TensorFlow now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
