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# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Module for performance estimation."""
from abc import abstractmethod
from typing import Callable
from typing import Generic
from typing import List
from typing import TypeVar
ModelType = TypeVar("ModelType") # pylint: disable=invalid-name
PerfMetricsType = TypeVar("PerfMetricsType") # pylint: disable=invalid-name
class PerformanceEstimator(Generic[ModelType, PerfMetricsType]):
"""Base class for the performance estimation."""
@abstractmethod
def estimate(self, model: ModelType) -> PerfMetricsType:
"""Estimate performance."""
def estimate_performance(
original_model: ModelType,
estimator: PerformanceEstimator[ModelType, PerfMetricsType],
model_transformations: List[Callable[[ModelType], ModelType]],
) -> List[PerfMetricsType]:
"""Estimate performance impact.
This function estimates performance impact on model performance after
applying provided transformations/optimizations.
:param original_model: object that represents a model, could be
instance of the model or path to the model. This depends on
provided performance estimator.
:param estimator: performance estimator
:param model_transformations: list of the callables each of those
returns object that represents optimized model
"""
original_metrics = estimator.estimate(original_model)
optimized_metrics = [
estimator.estimate(transform(original_model))
for transform in model_transformations
]
return [original_metrics, *optimized_metrics]
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