TensorFlow computational graph

When thinking of executing a TensorFlow program, we should be familiar with the concepts of graph creation and session execution. Basically, the first one is for building the model, and the second one is for feeding the data in and getting the results.

Interestingly, TensorFlow does everything on the C++ engine, which means not even a little multiplication or addition is executed in Python. Python is just a wrapper. Fundamentally, the TensorFlow C++ engine consists of the following two things:

  • Efficient implementations of operations, such as convolution, max pool, and sigmoid for a CNN for example
  • Derivatives of the forwarding mode operation

The TensorFlow lib is an extraordinary lib in terms of coding and it is not ...

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