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authorDmitrii Agibov <dmitrii.agibov@arm.com>2022-09-08 14:24:39 +0100
committerDmitrii Agibov <dmitrii.agibov@arm.com>2022-09-09 17:21:48 +0100
commitf5b293d0927506c2a979a091bf0d07ecc78fa181 (patch)
tree4de585b7cb6ed34da8237063752270189a730a41 /tests/test_nn_tensorflow_optimizations_clustering.py
parentcde0c6ee140bd108849bff40467d8f18ffc332ef (diff)
downloadmlia-f5b293d0927506c2a979a091bf0d07ecc78fa181.tar.gz
MLIA-386 Simplify typing in the source code
- Enable deferred annotations evaluation - Use builtin types for type hints whenever possible - Use | syntax for union types - Rename mlia.core._typing into mlia.core.typing Change-Id: I3f6ffc02fa069c589bdd9e8bddbccd504285427a
Diffstat (limited to 'tests/test_nn_tensorflow_optimizations_clustering.py')
-rw-r--r--tests/test_nn_tensorflow_optimizations_clustering.py12
1 files changed, 6 insertions, 6 deletions
diff --git a/tests/test_nn_tensorflow_optimizations_clustering.py b/tests/test_nn_tensorflow_optimizations_clustering.py
index c12a1e8..13dfb31 100644
--- a/tests/test_nn_tensorflow_optimizations_clustering.py
+++ b/tests/test_nn_tensorflow_optimizations_clustering.py
@@ -1,9 +1,9 @@
# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Test for module optimizations/clustering."""
+from __future__ import annotations
+
from pathlib import Path
-from typing import List
-from typing import Optional
import pytest
import tensorflow as tf
@@ -21,7 +21,7 @@ from tests.utils.common import train_model
def _prune_model(
- model: tf.keras.Model, target_sparsity: float, layers_to_prune: Optional[List[str]]
+ model: tf.keras.Model, target_sparsity: float, layers_to_prune: list[str] | None
) -> tf.keras.Model:
x_train, y_train = get_dataset()
batch_size = 1
@@ -47,7 +47,7 @@ def _prune_model(
def _test_num_unique_weights(
metrics: TFLiteMetrics,
target_num_clusters: int,
- layers_to_cluster: Optional[List[str]],
+ layers_to_cluster: list[str] | None,
) -> None:
clustered_uniqueness_dict = metrics.num_unique_weights(
ReportClusterMode.NUM_CLUSTERS_PER_AXIS
@@ -71,7 +71,7 @@ def _test_num_unique_weights(
def _test_sparsity(
metrics: TFLiteMetrics,
target_sparsity: float,
- layers_to_cluster: Optional[List[str]],
+ layers_to_cluster: list[str] | None,
) -> None:
pruned_sparsity_dict = metrics.sparsity_per_layer()
num_sparse_layers = 0
@@ -95,7 +95,7 @@ def _test_sparsity(
def test_cluster_simple_model_fully(
target_num_clusters: int,
sparsity_aware: bool,
- layers_to_cluster: Optional[List[str]],
+ layers_to_cluster: list[str] | None,
tmp_path: Path,
test_keras_model: Path,
) -> None: