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# SPDX-FileCopyrightText: Copyright 2022-2024, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Tests for Ethos-U data analysis module."""
from __future__ import annotations
from typing import cast
import pytest
from mlia.backend.vela.compat import NpuSupported
from mlia.backend.vela.compat import Operator
from mlia.backend.vela.compat import Operators
from mlia.backend.vela.performance import LayerwisePerfInfo
from mlia.core.common import DataItem
from mlia.core.data_analysis import Fact
from mlia.nn.select import OptimizationSettings
from mlia.nn.tensorflow.tflite_compat import TFLiteCompatibilityInfo
from mlia.nn.tensorflow.tflite_compat import TFLiteCompatibilityStatus
from mlia.nn.tensorflow.tflite_compat import TFLiteConversionError
from mlia.nn.tensorflow.tflite_compat import TFLiteConversionErrorCode
from mlia.target.common.reporters import ModelHasCustomOperators
from mlia.target.common.reporters import ModelIsNotTFLiteCompatible
from mlia.target.common.reporters import TFLiteCompatibilityCheckFailed
from mlia.target.ethos_u.config import EthosUConfiguration
from mlia.target.ethos_u.data_analysis import AllOperatorsSupportedOnNPU
from mlia.target.ethos_u.data_analysis import EthosUDataAnalyzer
from mlia.target.ethos_u.data_analysis import HasCPUOnlyOperators
from mlia.target.ethos_u.data_analysis import HasUnsupportedOnNPUOperators
from mlia.target.ethos_u.data_analysis import OptimizationDiff
from mlia.target.ethos_u.data_analysis import OptimizationResults
from mlia.target.ethos_u.data_analysis import PerfMetricDiff
from mlia.target.ethos_u.performance import MemoryUsage
from mlia.target.ethos_u.performance import NPUCycles
from mlia.target.ethos_u.performance import OptimizationPerformanceMetrics
from mlia.target.ethos_u.performance import PerformanceMetrics
from mlia.target.registry import profile
def test_perf_metrics_diff() -> None:
"""Test PerfMetricsDiff class."""
diff_same = PerfMetricDiff(1, 1)
assert diff_same.same is True
assert diff_same.improved is False
assert diff_same.degraded is False
assert diff_same.diff == 0
diff_improved = PerfMetricDiff(10, 5)
assert diff_improved.same is False
assert diff_improved.improved is True
assert diff_improved.degraded is False
assert diff_improved.diff == 50.0
diff_degraded = PerfMetricDiff(5, 10)
assert diff_degraded.same is False
assert diff_degraded.improved is False
assert diff_degraded.degraded is True
assert diff_degraded.diff == -100.0
diff_original_zero = PerfMetricDiff(0, 1)
assert diff_original_zero.diff == 0
@pytest.mark.parametrize(
"input_data, expected_facts",
[
[
Operators(
[
Operator(
"CPU operator",
"CPU operator type",
NpuSupported(False, [("CPU only operator", "")]),
)
]
),
[
HasCPUOnlyOperators(["CPU operator type"]),
HasUnsupportedOnNPUOperators(1.0),
],
],
[
Operators(
[
Operator(
"NPU operator",
"NPU operator type",
NpuSupported(True, []),
)
]
),
[
AllOperatorsSupportedOnNPU(),
],
],
[
OptimizationPerformanceMetrics(
PerformanceMetrics(
cast(EthosUConfiguration, profile("ethos-u55-256")),
NPUCycles(1, 2, 3, 4, 5, 6),
# memory metrics are in kilobytes
MemoryUsage(*[i * 1024 for i in range(1, 6)]), # type: ignore
LayerwisePerfInfo(layerwise_info=[]),
),
[
[
[
OptimizationSettings("pruning", 0.5, None),
],
PerformanceMetrics(
cast(EthosUConfiguration, profile("ethos-u55-256")),
NPUCycles(1, 2, 3, 4, 5, 6),
# memory metrics are in kilobytes
MemoryUsage(
*[i * 1024 for i in range(1, 6)] # type: ignore
),
LayerwisePerfInfo(layerwise_info=[]),
),
],
],
),
[
OptimizationResults(
[
OptimizationDiff(
opt_type=[
OptimizationSettings("pruning", 0.5, None),
],
opt_diffs={
"sram": PerfMetricDiff(1.0, 1.0),
"dram": PerfMetricDiff(2.0, 2.0),
"on_chip_flash": PerfMetricDiff(4.0, 4.0),
"off_chip_flash": PerfMetricDiff(5.0, 5.0),
"npu_total_cycles": PerfMetricDiff(3, 3),
},
)
]
)
],
],
[
OptimizationPerformanceMetrics(
PerformanceMetrics(
cast(EthosUConfiguration, profile("ethos-u55-256")),
NPUCycles(1, 2, 3, 4, 5, 6),
# memory metrics are in kilobytes
MemoryUsage(*[i * 1024 for i in range(1, 6)]), # type: ignore
LayerwisePerfInfo(layerwise_info=[]),
),
[],
),
[],
],
[
TFLiteCompatibilityInfo(status=TFLiteCompatibilityStatus.COMPATIBLE),
[],
],
[
TFLiteCompatibilityInfo(
status=TFLiteCompatibilityStatus.MODEL_WITH_CUSTOM_OP_ERROR
),
[ModelHasCustomOperators()],
],
[
TFLiteCompatibilityInfo(status=TFLiteCompatibilityStatus.UNKNOWN_ERROR),
[TFLiteCompatibilityCheckFailed()],
],
[
TFLiteCompatibilityInfo(
status=TFLiteCompatibilityStatus.TFLITE_CONVERSION_ERROR
),
[ModelIsNotTFLiteCompatible(custom_ops=[], flex_ops=[])],
],
[
TFLiteCompatibilityInfo(
status=TFLiteCompatibilityStatus.TFLITE_CONVERSION_ERROR,
conversion_errors=[
TFLiteConversionError(
"error",
TFLiteConversionErrorCode.NEEDS_CUSTOM_OPS,
"custom_op1",
[],
),
TFLiteConversionError(
"error",
TFLiteConversionErrorCode.NEEDS_FLEX_OPS,
"flex_op1",
[],
),
],
),
[
ModelIsNotTFLiteCompatible(
custom_ops=["custom_op1"],
flex_ops=["flex_op1"],
)
],
],
],
)
def test_ethos_u_data_analyzer(
input_data: DataItem, expected_facts: list[Fact]
) -> None:
"""Test Ethos-U data analyzer."""
analyzer = EthosUDataAnalyzer()
analyzer.analyze_data(input_data)
assert analyzer.get_analyzed_data() == expected_facts
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