Title: Theory / Important / CS / Programming / Python / TensorFlow
Tags: seen_description automatedNewLineAfterCommaSpace
On every note of this deck, unless a note says otherwise:
Page: https://colab.research.google.com/notebooks/mlcc/tensorflow_programming_concepts.ipynb
Page: https://colab.research.google.com/notebooks/mlcc/tensorflow_programming_concepts.ipynb

Name: Tensor
Definition: An array of arbitrary dimension
Context: Tensorflow

Name: An operation
Definition: Creating, destroying or manipulation tensors
Context: TensorFlow

Name: TensorFlow graph
Definition: node are tensorflow operations
Context: TensorFlow
Definition2: edges are tensor
Conjdef: A graph with
Name2: Computational graph
Name3: Dataflow graph

Name: Constant node
Definition: A tensor that can't change (an operation without input)
Context: TensorFlow

Name: A variable node
Definition: A node which is not constant
Context: TensorFlow

Instruction: constants(foo)
Effect: A constant node whose value is foo
Language: TensorFlow

Instruction: Variable(foo)
Effect: A variable node whose initial value is foo
Language: TensorFlow

Name: Session
Definition: A structure holding the state of a tensorflow graph
Context: Tensorflow
Intuition: Can distribute graph execution across multiple machines (assuming the program is run on some distributed computation framework

Instruction: with tf.Sessions() as sess:
Effect: Open a tensorflow session
Context: Tensorflow

Instruction: Graph()
Context: Tensorflow
Returns: A new graph

Instruction: with g.as_default():
  foo
Effect: Each operation of foo are assumed in the graph g by default
Context: Tensorflow
Variables: g a graph

Instruction: add(
  foo,
  bar
)
Effect: A variable node with pointwise sum of elements foo and bar
Context: Tensorflow

Instruction: n.eval()
Effect: Compute the value of n and all required intermediate nodes' value
Context: Tensorflow
Variables: n a node