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Add Documentation for profiling in TFLite Micro.

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Nat Jeffries 2020-11-05 13:24:49 -08:00 committed by TensorFlower Gardener
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tensorflow/lite/micro/README.md
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project, we have additional documentation in the [docs](docs/) folder.
* [Benchmarks](benchmarks/README.md)
* [Profiling](docs/profiling.md)
* [Memory Management](docs/memory_management.md)
* [New Platform Support](docs/new_platform_support.md)
* [Software Emulation with Renode](docs/renode.md)

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* [Profiling](#profiling)
* [API](#api)
* [Per-Op Profiling](#per-op-profiling)
* [Subroutine Profiling](#subroutine-profiling)
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# Profiling
This doc outlines how to use the TFLite Micro profiler to gather information
about per-op invoke duration and to use the profiler to identify bottlenecks
from within operator kernels and other TFLite Micro routines.
## API
The MicroInterpreter class constructor contains and optional profiler argument.
This profiler must be an instance of the tflite::Profiler class, and should
implement the BeginEvent and EndEvent methods. There is a default implementation
in tensorflow/lite/micro/micro_profiler.cc which can be used for most purposes.
## Per-Op Profiling
There is a feature in the MicroInterpreter to enable per-op profiling. To enable
this, provide a MicroProfiler to the MicroInterpreter's constructor then build
with a non-release build to disable the NDEBUG define surrounding the
ScopedOperatorProfile within the MicroInterpreter.
## Subroutine Profiling
In order to further dig into performance of specific routines, the MicroProfiler
can be used directly from the TFLiteContext or a new MicroProfiler can be
created if the TFLiteContext is not available where the profiling needs to
happen. The MicroProfiler's BeginEvent and EndEvent can be called directly, or
wrapped using a [ScopedProfile](../../lite/core/api/profiler.h).