Inputs, variables, outputs, and operations
Now we are returning from our journey into TensorFlow 1 and stepping back to TensorFlow 2. Let’s proceed to the most common elements that comprise a TensorFlow 2 program. If you read any of the millions of TensorFlow clients available on the internet, the TensorFlow-related code all falls 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 sigmoid example, we can find instances of all these categories. We list the respective TensorFlow elements and the notation used in the sigmoid example in Table 2.1:
|
TensorFlow element |
Value from example client ... |
