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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 collections import defaultdict
from dataclasses import dataclass
from dataclasses import field
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.devices.cortexa.operators import Operator
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(data_item.backend_info))
else:
unsupported_ops = set()
activation_func_support: defaultdict[
str, ModelIsNotCortexACompatible.ActivationFunctionSupport
] = defaultdict(ModelIsNotCortexACompatible.ActivationFunctionSupport)
for oper in data_item.operators:
if oper.support_type == Operator.SupportType.OP_NOT_SUPPORTED:
unsupported_ops.add(oper.full_name)
if oper.support_type == Operator.SupportType.ACTIVATION_NOT_SUPPORTED:
# Add used but unsupported actication functions
activation_func_support[oper.full_name].used_unsupported.add(
oper.activation_func.name
)
# Add supported activation functions
activation_func_support[oper.full_name].supported.update(
oper.supported_activation_functions
)
assert (
unsupported_ops or activation_func_support or not data_item.operators
), (
"The model is marked as not compatible with Cortex-A but there "
"are no unsupported ops activation functions listed."
)
self.add_fact(
ModelIsNotCortexACompatible(
data_item.backend_info, unsupported_ops, activation_func_support
)
)
@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 CortexACompatibility(Fact):
"""Base class for Cortex-A compatibility providing backend info."""
backend_info: str
@dataclass
class ModelIsCortexACompatible(CortexACompatibility):
"""Model is completely compatible with Cortex-A."""
@dataclass
class ModelIsNotCortexACompatible(CortexACompatibility):
"""Model is not compatible with Cortex-A."""
@dataclass
class ActivationFunctionSupport:
"""Activation function support per operator."""
used_unsupported: set[str] = field(default_factory=set)
supported: set[str] = field(default_factory=set)
unsupported_ops: set[str]
activation_func_support: dict[str, ActivationFunctionSupport]
@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
|
