What is Static Subgraph Optimizations in Usage and Design Notes in chainer

This recipe explains what is Static Subgraph Optimizations in Usage and Design Notes in chainer

Recipe Objective - What is Static Subgraph Optimizations in Usage and Design Notes in chainer?

Static Subgraph Optimizations: Usage

This feature plans to improve runtime execution by enhancing the execution of the static subgraphs in a model.

At the point when this element is empowered, the principal cycle runs as typical with the exception of that an execution follow is likewise gathered.

The following is then used to create advanced code that is will be called instead of the define-by-run code starting from the second iteration.

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Basic Usage:-

To enable static graph optimizations, it is only necessary to add the chainer.static_graph() decorator to a chain’s __call__() method.

We will now show how the Chainer MNIST example can be modified to use this feature.


Import the necessary packages:
from chainer import static_code
from chainer import static_graph

Disabling the static subgraph optimization:

It is possible to turn off the static subgraph optimization feature by setting the "chainer.config.use_static_graph" to "False".

If set to "False", the "chainer.static_graph()" decorator will simply call the wrapped function without any further side effects.

Static Subgraph Optimizations: Design Notes

This documentation is planned to give data on the engineering and plan of the static subgraph enhancements include for those keen on adding to its turn of events.

This documentation also describes how existing Chainer capacities can be changed to run all the more proficiently when static subgraph optimizations are enabled.

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