Rename modules

- Rename module "mlia.devices" into "mlia.target"
- Rename module "mlia.target.ethosu" into "mlia.target.ethos_u"
- Rename module "mlia.target.cortexa" into "mlia.target.cortex_a"
- Rename and update tests

Change-Id: I6dca7c8646d881f739fb6b5914d1cc7e45e63dc2

1 files changed, 0 insertions, 187 deletions

diff --git a/src/mlia/devices/ethosu/data_collection.py b/src/mlia/devices/ethosu/data_collection.py
deleted file mode 100644
index d68eadb..0000000
--- a/src/mlia/devices/ethosu/data_collection.py
+++ /dev/null
@@ -1,187 +0,0 @@
-# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
-# SPDX-License-Identifier: Apache-2.0
-"""Data collection module for Ethos-U."""
-from __future__ import annotations
-
-import logging
-from pathlib import Path
-
-from mlia.backend.vela.compat import Operators
-from mlia.backend.vela.compat import supported_operators
-from mlia.core.context import Context
-from mlia.core.data_collection import ContextAwareDataCollector
-from mlia.core.errors import FunctionalityNotSupportedError
-from mlia.core.performance import estimate_performance
-from mlia.devices.ethosu.config import EthosUConfiguration
-from mlia.devices.ethosu.performance import EthosUPerformanceEstimator
-from mlia.devices.ethosu.performance import OptimizationPerformanceMetrics
-from mlia.devices.ethosu.performance import PerformanceMetrics
-from mlia.nn.tensorflow.config import get_keras_model
-from mlia.nn.tensorflow.config import get_tflite_model
-from mlia.nn.tensorflow.config import KerasModel
-from mlia.nn.tensorflow.optimizations.select import get_optimizer
-from mlia.nn.tensorflow.optimizations.select import OptimizationSettings
-from mlia.nn.tensorflow.utils import save_keras_model
-from mlia.utils.logging import log_action
-from mlia.utils.types import is_list_of
-
-logger = logging.getLogger(__name__)
-
-
-class EthosUOperatorCompatibility(ContextAwareDataCollector):
-    """Collect operator compatibility information."""
-
-    def __init__(self, model: Path, device: EthosUConfiguration) -> None:
-        """Init operator compatibility data collector."""
-        self.model = model
-        self.device = device
-
-    def collect_data(self) -> Operators:
-        """Collect operator compatibility information."""
-        tflite_model = get_tflite_model(self.model, self.context)
-
-        with log_action("Checking operator compatibility ..."):
-            return supported_operators(
-                Path(tflite_model.model_path), self.device.compiler_options
-            )
-
-    @classmethod
-    def name(cls) -> str:
-        """Return name of the collector."""
-        return "ethos_u_operator_compatibility"
-
-
-class EthosUPerformance(ContextAwareDataCollector):
-    """Collect performance metrics."""
-
-    def __init__(
-        self,
-        model: Path,
-        device: EthosUConfiguration,
-        backends: list[str] | None = None,
-    ) -> None:
-        """Init performance data collector."""
-        self.model = model
-        self.device = device
-        self.backends = backends
-
-    def collect_data(self) -> PerformanceMetrics:
-        """Collect model performance metrics."""
-        tflite_model = get_tflite_model(self.model, self.context)
-        estimator = EthosUPerformanceEstimator(
-            self.context,
-            self.device,
-            self.backends,
-        )
-
-        return estimator.estimate(tflite_model)
-
-    @classmethod
-    def name(cls) -> str:
-        """Return name of the collector."""
-        return "ethos_u_performance"
-
-
-class OptimizeModel:
-    """Helper class for model optimization."""
-
-    def __init__(
-        self, context: Context, opt_settings: list[OptimizationSettings]
-    ) -> None:
-        """Init helper."""
-        self.context = context
-        self.opt_settings = opt_settings
-
-    def __call__(self, keras_model: KerasModel) -> KerasModel:
-        """Run optimization."""
-        optimizer = get_optimizer(keras_model, self.opt_settings)
-
-        opts_as_str = ", ".join(str(opt) for opt in self.opt_settings)
-        logger.info("Applying model optimizations - [%s]", opts_as_str)
-        optimizer.apply_optimization()
-
-        model = optimizer.get_model()
-        model_path = self.context.get_model_path("optimized_model.h5")
-        save_keras_model(model, model_path)
-
-        return KerasModel(model_path)
-
-
-class EthosUOptimizationPerformance(ContextAwareDataCollector):
-    """Collect performance metrics for the optimizations."""
-
-    def __init__(
-        self,
-        model: Path,
-        device: EthosUConfiguration,
-        optimizations: list[list[dict]],
-        backends: list[str] | None = None,
-    ) -> None:
-        """Init performance optimizations data collector."""
-        self.model = model
-        self.device = device
-        self.optimizations = optimizations
-        self.backends = backends
-
-    def collect_data(self) -> OptimizationPerformanceMetrics | None:
-        """Collect performance metrics for the optimizations."""
-        logger.info("Estimate performance ...")
-
-        if not self.optimizations:
-            raise FunctionalityNotSupportedError(
-                reason="Unable to estimate model optimizations impact",
-                description="No optimization targets provided",
-            )
-
-        opt_settings = self._parse_optimization_params(self.optimizations)
-
-        try:
-            keras_model = get_keras_model(self.model, self.context)
-        except NotImplementedError as err:
-            raise FunctionalityNotSupportedError(
-                reason="Unable to run model optimizations",
-                description=f"{self.model} is not a Keras model and "
-                "could not be converted to a Keras model",
-            ) from err
-
-        optimizers = [OptimizeModel(self.context, opts) for opts in opt_settings]
-
-        estimator = EthosUPerformanceEstimator(
-            self.context,
-            self.device,
-            self.backends,
-        )
-        original_metrics, *optimized_metrics = estimate_performance(
-            keras_model, estimator, optimizers  # type: ignore
-        )
-
-        result = OptimizationPerformanceMetrics(
-            original_perf_metrics=original_metrics,
-            optimizations_perf_metrics=list(zip(opt_settings, optimized_metrics)),
-        )
-        return result
-
-    @staticmethod
-    def _parse_optimization_params(
-        optimizations: list[list[dict]],
-    ) -> list[list[OptimizationSettings]]:
-        """Parse optimization parameters."""
-        if not is_list_of(optimizations, list):
-            raise Exception("Optimization parameters expected to be a list")
-
-        return [
-            [
-                OptimizationSettings(
-                    item.get("optimization_type"),  # type: ignore
-                    item.get("optimization_target"),  # type: ignore
-                    item.get("layers_to_optimized"),
-                )
-                for item in opt_configuration
-            ]
-            for opt_configuration in optimizations
-        ]
-
-    @classmethod
-    def name(cls) -> str:
-        """Return name of the collector."""
-        return "ethos_u_model_optimizations"