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# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Cortex-A data analysis module."""
from __future__ import annotations
from dataclasses import dataclass
from functools import singledispatchmethod
from mlia.core.common import DataItem
from mlia.core.data_analysis import Fact
from mlia.core.data_analysis import FactExtractor
from mlia.devices.cortexa.operators import CortexACompatibilityInfo
from mlia.nn.tensorflow.tflite_compat import TFLiteCompatibilityInfo
from mlia.nn.tensorflow.tflite_compat import TFLiteConversionErrorCode
class CortexADataAnalyzer(FactExtractor):
"""Cortex-A data analyzer."""
@singledispatchmethod
def analyze_data(self, data_item: DataItem) -> None:
"""Analyse the data."""
@analyze_data.register
def analyze_operator_compatibility(
self, data_item: CortexACompatibilityInfo
) -> None:
"""Analyse operator compatibility information."""
if data_item.cortex_a_compatible:
self.add_fact(ModelIsCortexACompatible())
else:
self.add_fact(ModelIsNotCortexACompatible())
@analyze_data.register
def analyze_tflite_compatibility(self, data_item: TFLiteCompatibilityInfo) -> None:
"""Analyze TensorFlow Lite compatibility information."""
if data_item.compatible:
return
custom_ops, flex_ops = [], []
if data_item.conversion_errors:
custom_ops = data_item.unsupported_ops_by_code(
TFLiteConversionErrorCode.NEEDS_CUSTOM_OPS
)
flex_ops = data_item.unsupported_ops_by_code(
TFLiteConversionErrorCode.NEEDS_FLEX_OPS
)
self.add_fact(
ModelIsNotTFLiteCompatible(custom_ops=custom_ops, flex_ops=flex_ops)
)
@dataclass
class ModelIsCortexACompatible(Fact):
"""Model is completely compatible with Cortex-A."""
@dataclass
class ModelIsNotCortexACompatible(Fact):
"""Model is not compatible with Cortex-A."""
@dataclass
class ModelIsNotTFLiteCompatible(Fact):
"""Model could not be converted into TensorFlow Lite format."""
custom_ops: list[str] | None = None
flex_ops: list[str] | None = None
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