MLIA-551 Rework remains of AIET architecture

Re-factoring the code base to further merge the old AIET code into MLIA.

- Remove last traces of the backend type 'tool'
- Controlled systems removed, including SSH protocol, controller,
  RunningCommand, locks etc.
- Build command / build dir and deploy functionality removed from
  Applications and Systems
- Moving working_dir()
- Replace module 'output_parser' with new module 'output_consumer' and
  merge Base64 parsing into it
- Change the output consumption to optionally remove (i.e. actually
  consume) lines
- Use Base64 parsing in GenericInferenceOutputParser, replacing the
  regex-based parsing and remove the now unused regex parsing
- Remove AIET reporting
- Pre-install applications by moving them to src/mlia/resources/backends
- Rename aiet-config.json to backend-config.json
- Move tests from tests/mlia/ to tests/
- Adapt unit tests to code changes
- Dependencies removed: paramiko, filelock, psutil
- Fix bug in corstone.py: The wrong resource directory was used which
  broke the functionality to download backends.
- Use f-string formatting.
- Use logging instead of print.

Change-Id: I768bc3bb6b2eda57d219ad01be4a8e0a74167d76

1 files changed, 81 insertions, 0 deletions

diff --git a/tests/test_nn_tensorflow_utils.py b/tests/test_nn_tensorflow_utils.py
new file mode 100644
index 0000000..6d27299
--- /dev/null
+++ b/tests/test_nn_tensorflow_utils.py
@@ -0,0 +1,81 @@
+# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0
+"""Test for module utils/test_utils."""
+from pathlib import Path
+
+import pytest
+import tensorflow as tf
+
+from mlia.nn.tensorflow.utils import convert_to_tflite
+from mlia.nn.tensorflow.utils import get_tf_tensor_shape
+from mlia.nn.tensorflow.utils import is_keras_model
+from mlia.nn.tensorflow.utils import is_tflite_model
+from mlia.nn.tensorflow.utils import save_keras_model
+from mlia.nn.tensorflow.utils import save_tflite_model
+
+
+def test_convert_to_tflite(test_keras_model: Path) -> None:
+    """Test converting Keras model to TFLite."""
+    keras_model = tf.keras.models.load_model(str(test_keras_model))
+    tflite_model = convert_to_tflite(keras_model)
+
+    assert tflite_model
+
+
+def test_save_keras_model(tmp_path: Path, test_keras_model: Path) -> None:
+    """Test saving Keras model."""
+    keras_model = tf.keras.models.load_model(str(test_keras_model))
+
+    temp_file = tmp_path / "test_model_saving.h5"
+    save_keras_model(keras_model, temp_file)
+    loaded_model = tf.keras.models.load_model(temp_file)
+
+    assert loaded_model.summary() == keras_model.summary()
+
+
+def test_save_tflite_model(tmp_path: Path, test_keras_model: Path) -> None:
+    """Test saving TFLite model."""
+    keras_model = tf.keras.models.load_model(str(test_keras_model))
+
+    tflite_model = convert_to_tflite(keras_model)
+
+    temp_file = tmp_path / "test_model_saving.tflite"
+    save_tflite_model(tflite_model, temp_file)
+
+    interpreter = tf.lite.Interpreter(model_path=str(temp_file))
+    assert interpreter
+
+
+@pytest.mark.parametrize(
+    "model_path, expected_result",
+    [
+        [Path("sample_model.tflite"), True],
+        [Path("strange_model.tflite.tfl"), False],
+        [Path("sample_model.h5"), False],
+        [Path("sample_model"), False],
+    ],
+)
+def test_is_tflite_model(model_path: Path, expected_result: bool) -> None:
+    """Test function is_tflite_model."""
+    result = is_tflite_model(model_path)
+    assert result == expected_result
+
+
+@pytest.mark.parametrize(
+    "model_path, expected_result",
+    [
+        [Path("sample_model.h5"), True],
+        [Path("strange_model.h5.keras"), False],
+        [Path("sample_model.tflite"), False],
+        [Path("sample_model"), False],
+    ],
+)
+def test_is_keras_model(model_path: Path, expected_result: bool) -> None:
+    """Test function is_keras_model."""
+    result = is_keras_model(model_path)
+    assert result == expected_result
+
+
+def test_get_tf_tensor_shape(test_tf_model: Path) -> None:
+    """Test get_tf_tensor_shape with test model."""
+    assert get_tf_tensor_shape(str(test_tf_model)) == [1, 28, 28, 1]