feat: Enable rewrite parameterisation

Enables user to provide a toml or default profile to change training settings for rewrite optimization

Resolves: MLIA-1004

Signed-off-by: Nathan Bailey <nathan.bailey@arm.com>
Change-Id: I3bf9f44b9a2062fb71ef36eb32c9a69edcc48061

1 files changed, 66 insertions, 3 deletions

diff --git a/tests/test_nn_select.py b/tests/test_nn_select.py
index 31628d2..92b7a3d 100644
--- a/tests/test_nn_select.py
+++ b/tests/test_nn_select.py
@@ -1,16 +1,21 @@
-# SPDX-FileCopyrightText: Copyright 2022-2023, Arm Limited and/or its affiliates.
+# SPDX-FileCopyrightText: Copyright 2022-2024, Arm Limited and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 """Tests for module select."""
 from __future__ import annotations
 
 from contextlib import ExitStack as does_not_raise
+from dataclasses import asdict
 from pathlib import Path
 from typing import Any
+from typing import cast
 
 import pytest
 import tensorflow as tf
 
 from mlia.core.errors import ConfigurationError
+from mlia.nn.rewrite.core.rewrite import RewriteConfiguration
+from mlia.nn.rewrite.core.rewrite import RewritingOptimizer
+from mlia.nn.rewrite.core.rewrite import TrainingParameters
 from mlia.nn.select import get_optimizer
 from mlia.nn.select import MultiStageOptimizer
 from mlia.nn.select import OptimizationSettings
@@ -135,6 +140,23 @@ from mlia.nn.tensorflow.optimizations.pruning import PruningConfiguration
             MultiStageOptimizer,
             "pruning: 0.5 - clustering: 32",
         ),
+        (
+            OptimizationSettings(
+                optimization_type="rewrite",
+                optimization_target="fully_connected",  # type: ignore
+                layers_to_optimize=None,
+                dataset=None,
+            ),
+            does_not_raise(),
+            RewritingOptimizer,
+            "rewrite: fully_connected",
+        ),
+        (
+            RewriteConfiguration("fully_connected"),
+            does_not_raise(),
+            RewritingOptimizer,
+            "rewrite: fully_connected",
+        ),
     ],
 )
 def test_get_optimizer(
@@ -143,17 +165,58 @@ def test_get_optimizer(
     expected_type: type,
     expected_config: str,
     test_keras_model: Path,
+    test_tflite_model: Path,
 ) -> None:
     """Test function get_optimzer."""
-    model = tf.keras.models.load_model(str(test_keras_model))
-
     with expected_error:
+        if (
+            isinstance(config, OptimizationSettings)
+            and config.optimization_type == "rewrite"
+        ) or isinstance(config, RewriteConfiguration):
+            model = test_tflite_model
+        else:
+            model = tf.keras.models.load_model(str(test_keras_model))
         optimizer = get_optimizer(model, config)
         assert isinstance(optimizer, expected_type)
         assert optimizer.optimization_config() == expected_config
 
 
 @pytest.mark.parametrize(
+    "rewrite_parameters",
+    [[None], [{"batch_size": 64, "learning_rate": 0.003}]],
+)
+@pytest.mark.skip_set_training_steps
+def test_get_optimizer_training_parameters(
+    rewrite_parameters: list[dict], test_tflite_model: Path
+) -> None:
+    """Test function get_optimzer with various combinations of parameters."""
+    config = OptimizationSettings(
+        optimization_type="rewrite",
+        optimization_target="fully_connected",  # type: ignore
+        layers_to_optimize=None,
+        dataset=None,
+    )
+    optimizer = cast(
+        RewritingOptimizer,
+        get_optimizer(test_tflite_model, config, list(rewrite_parameters)),
+    )
+
+    assert len(rewrite_parameters) == 1
+
+    assert isinstance(
+        optimizer.optimizer_configuration.train_params, TrainingParameters
+    )
+    if not rewrite_parameters[0]:
+        assert asdict(TrainingParameters()) == asdict(
+            optimizer.optimizer_configuration.train_params
+        )
+    else:
+        assert asdict(TrainingParameters()) | rewrite_parameters[0] == asdict(
+            optimizer.optimizer_configuration.train_params
+        )
+
+
+@pytest.mark.parametrize(
     "params, expected_result",
     [
         (