MLIA-835 Invalid JSON output

TFLiteConverter was producing log messages in the output that was not
possible to capture and redirect to logging.
The solution/workaround is to run it as a subprocess.

This change required some refactoring around existing invocations of
the converter.

Change-Id: I394bd0d49d36e6686cfcb9d658e4aad05326cb87
Signed-off-by: Gergely Nagy <gergely.nagy@arm.com>

1 files changed, 3 insertions, 4 deletions

diff --git a/tests/test_nn_tensorflow_optimizations_pruning.py b/tests/test_nn_tensorflow_optimizations_pruning.py
index d97b3d3..9afc3ff 100644
--- a/tests/test_nn_tensorflow_optimizations_pruning.py
+++ b/tests/test_nn_tensorflow_optimizations_pruning.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
+# SPDX-FileCopyrightText: Copyright 2022-2023, Arm Limited and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 """Test for module optimizations/pruning."""
 from __future__ import annotations
@@ -11,9 +11,8 @@ from numpy.core.numeric import isclose
 
 from mlia.nn.tensorflow.optimizations.pruning import Pruner
 from mlia.nn.tensorflow.optimizations.pruning import PruningConfiguration
+from mlia.nn.tensorflow.tflite_convert import convert_to_tflite
 from mlia.nn.tensorflow.tflite_metrics import TFLiteMetrics
-from mlia.nn.tensorflow.utils import convert_to_tflite
-from mlia.nn.tensorflow.utils import save_tflite_model
 from tests.utils.common import get_dataset
 from tests.utils.common import train_model
 
@@ -52,7 +51,7 @@ def _get_tflite_metrics(
 ) -> TFLiteMetrics:
     """Save model as TFLiteModel and return metrics."""
     temp_file = path / tflite_fn
-    save_tflite_model(convert_to_tflite(model), temp_file)
+    convert_to_tflite(model, output_path=temp_file)
     return TFLiteMetrics(str(temp_file))