Defining Inputs in TensorFlow

Learn about the different types of inputs in TensorFlow.


Now, we’re 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 we 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.

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