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, 14 insertions, 6 deletions

diff --git a/src/mlia/nn/tensorflow/config.py b/src/mlia/nn/tensorflow/config.py
index b94350a..0a17977 100644
--- a/src/mlia/nn/tensorflow/config.py
+++ b/src/mlia/nn/tensorflow/config.py
@@ -21,14 +21,13 @@ from mlia.nn.tensorflow.optimizations.quantization import dequantize
 from mlia.nn.tensorflow.optimizations.quantization import is_quantized
 from mlia.nn.tensorflow.optimizations.quantization import QuantizationParameters
 from mlia.nn.tensorflow.optimizations.quantization import quantize
+from mlia.nn.tensorflow.tflite_convert import convert_to_tflite
 from mlia.nn.tensorflow.tflite_graph import load_fb
 from mlia.nn.tensorflow.tflite_graph import save_fb
 from mlia.nn.tensorflow.utils import check_tflite_datatypes
-from mlia.nn.tensorflow.utils import convert_to_tflite
 from mlia.nn.tensorflow.utils import is_keras_model
 from mlia.nn.tensorflow.utils import is_saved_model
 from mlia.nn.tensorflow.utils import is_tflite_model
-from mlia.nn.tensorflow.utils import save_tflite_model
 from mlia.utils.logging import log_action
 
 logger = logging.getLogger(__name__)
@@ -67,9 +66,14 @@ class KerasModel(ModelConfiguration):
     ) -> TFLiteModel:
         """Convert model to TensorFlow Lite format."""
         with log_action("Converting Keras to TensorFlow Lite ..."):
-            converted_model = convert_to_tflite(self.get_keras_model(), quantized)
+            convert_to_tflite(
+                self.get_keras_model(),
+                quantized,
+                input_path=Path(self.model_path),
+                output_path=Path(tflite_model_path),
+                subprocess=True,
+            )
 
-        save_tflite_model(converted_model, tflite_model_path)
         logger.debug(
             "Model %s converted and saved to %s", self.model_path, tflite_model_path
         )
@@ -270,8 +274,12 @@ class TfModel(ModelConfiguration):  # pylint: disable=abstract-method
         self, tflite_model_path: str | Path, quantized: bool = False
     ) -> TFLiteModel:
         """Convert model to TensorFlow Lite format."""
-        converted_model = convert_to_tflite(self.model_path, quantized)
-        save_tflite_model(converted_model, tflite_model_path)
+        convert_to_tflite(
+            self.model_path,
+            quantized,
+            input_path=Path(self.model_path),
+            output_path=Path(tflite_model_path),
+        )
 
         return TFLiteModel(tflite_model_path)