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| author | Gergely Nagy <gergely.nagy@arm.com> | 2023-11-21 12:29:38 +0000 |
|---|---|---|
| committer | Gergely Nagy <gergely.nagy@arm.com> | 2023-12-07 17:09:31 +0000 |
| commit | 54eec806272b7574a0757c77a913a369a9ecdc70 (patch) | |
| tree | 2e6484b857b2a68279a2707dbb21e5c26685f4e2 /tests/test_nn_tensorflow_optimizations_clustering.py | |
| parent | 7c50f1d6367186c03a282ac7ecb8fca0f905ba30 (diff) | |
| download | mlia-54eec806272b7574a0757c77a913a369a9ecdc70.tar.gz | |
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>
Diffstat (limited to 'tests/test_nn_tensorflow_optimizations_clustering.py')
| -rw-r--r-- | tests/test_nn_tensorflow_optimizations_clustering.py | 6 |
1 files changed, 2 insertions, 4 deletions
diff --git a/tests/test_nn_tensorflow_optimizations_clustering.py b/tests/test_nn_tensorflow_optimizations_clustering.py index d3c0da6..58ffb3e 100644 --- a/tests/test_nn_tensorflow_optimizations_clustering.py +++ b/tests/test_nn_tensorflow_optimizations_clustering.py @@ -14,10 +14,9 @@ from mlia.nn.tensorflow.optimizations.clustering import Clusterer from mlia.nn.tensorflow.optimizations.clustering import ClusteringConfiguration 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 ReportClusterMode 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 @@ -118,8 +117,7 @@ def test_cluster_simple_model_fully( clustered_model = clusterer.get_model() temp_file = tmp_path / "test_cluster_simple_model_fully_after.tflite" - tflite_clustered_model = convert_to_tflite(clustered_model) - save_tflite_model(tflite_clustered_model, temp_file) + convert_to_tflite(clustered_model, output_path=temp_file) clustered_tflite_metrics = TFLiteMetrics(str(temp_file)) _test_num_unique_weights( |