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, 29 insertions, 0 deletions

diff --git a/tests/test_core_performance.py b/tests/test_core_performance.py
new file mode 100644
index 0000000..0d28fe8
--- /dev/null
+++ b/tests/test_core_performance.py
@@ -0,0 +1,29 @@
+# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0
+"""Tests for the module performance."""
+from pathlib import Path
+
+from mlia.core.performance import estimate_performance
+from mlia.core.performance import PerformanceEstimator
+
+
+def test_estimate_performance(tmp_path: Path) -> None:
+    """Test function estimate_performance."""
+    model_path = tmp_path / "original.tflite"
+
+    class SampleEstimator(PerformanceEstimator[Path, int]):
+        """Sample estimator."""
+
+        def estimate(self, model: Path) -> int:
+            """Estimate performance."""
+            if model.name == "original.tflite":
+                return 1
+
+            return 2
+
+    def optimized_model(_original: Path) -> Path:
+        """Return path to the 'optimized' model."""
+        return tmp_path / "optimized.tflite"
+
+    results = estimate_performance(model_path, SampleEstimator(), [optimized_model])
+    assert results == [1, 2]