April 2017
Intermediate to advanced
320 pages
7h 46m
English
Content preview from Deep Learning with TensorFlow
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How does TensorBoard work?
As explained, TensorFlow uses the computation graph to execute an application, where each node represents an operation and the arcs are the data between operations. The main idea in TensorBoard is to associate the so-called summary with nodes (operations) of the graph.
Running the code, the summary operations will serialize the data of the node that is associated with it, and output the data, into a file that can be read by TensorBoard.
Then we can run TensorBoard and visualize the summarized operations. The workflow when using TensorBoard is:
- Build your computational graph/code
- Attach summary ops to the nodes you are interested in examining
- Start running your graph as you normally would
- Additionally, run the summary ...
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