AI-generated Key Takeaways
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BenchmarkResult is a data class containing the results of a benchmark.
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It includes nested classes for BenchmarkMetric (accuracy metrics) and InferenceOutput (model output of one tensor).
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Public methods provide access to the actual model output, accuracy check status, inference and initialization times in microseconds, maximum memory usage in kilobytes, and a list of accuracy metrics.
Data class that contains BenchmarkResult.
Nested Class Summary
class | BenchmarkResult.BenchmarkMetric | Accuracy metrics. | |
class | BenchmarkResult.InferenceOutput | Model output of one tensor. |
Public Method Summary
abstract List<BenchmarkResult.InferenceOutput> |
actualOutput()
Returns model output of running with this config.
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abstract boolean |
hasPassedAccuracyCheck()
Returns whether accuracy validation check has passed.
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abstract List<Long> |
inferenceTimeMicros()
Returns inference time of each sample input, in microseconds.
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abstract List<Long> |
initializationTimeMicros()
Returns initialization time of each sample input, in microseconds.
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abstract int |
maxMemoryKb()
Returns max memory used of all sample inputs, in kilobytes.
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abstract List<BenchmarkResult.BenchmarkMetric> |
metrics()
Returns the list of accuracy metrics.
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Inherited Method Summary
Public Methods
public abstract List<BenchmarkResult.InferenceOutput> actualOutput ()
Returns model output of running with this config. Each
BenchmarkResult.InferenceOutput
maps to one output tensor.
public abstract boolean hasPassedAccuracyCheck ()
Returns whether accuracy validation check has passed.
public abstract List<Long> inferenceTimeMicros ()
Returns inference time of each sample input, in microseconds.
public abstract List<Long> initializationTimeMicros ()
Returns initialization time of each sample input, in microseconds.
public abstract int maxMemoryKb ()
Returns max memory used of all sample inputs, in kilobytes.
public abstract List<BenchmarkResult.BenchmarkMetric> metrics ()
Returns the list of accuracy metrics.