Which of the following is the computing model of TensorFlow?

Question

Options

• ACalculation chart
• BTensor
• CConversation
• DVariable

• A
  72% (41)
• B
  14% (8)
• C
  9% (5)
• D
  5% (3)

Explanation

Option A is correct because TensorFlow's core computing model is the dataflow graph (computation graph / "calculation chart"), where computations are represented as directed graphs: nodes are mathematical operations, and edges are the tensors (data) flowing between them. This graph-based model allows TensorFlow to optimize and parallelize execution before running.

Why the distractors are wrong:

• B (Tensor): Tensors are TensorFlow's fundamental data structure (multi-dimensional arrays), not the computing model itself.
• C (Conversation): This has no meaning in the TensorFlow context.
• D (Variable): Variables are a special tensor type used to store mutable state (e.g., model weights), but they are a data construct, not the computing model.

Memory tip: Split the name - "TensorFlow" - tensors flow through a graph (chart). The "flow" part directly hints at the dataflow graph model.

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