add test for gptq annealing cfg

tests_pytest/pytorch/gptq/test_annealing_cfg.py

@@ -0,0 +1,40 @@
+# Copyright 2024 Sony Semiconductor Israel, Inc. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+import pytest
+
+from model_compression_toolkit.gptq import LinearAnnealingConfig
+
+
+def test_linear_annealing_cfg_validation():
+    with pytest.raises(ValueError, match='Expected.* initial_factor <= 1'):
+        LinearAnnealingConfig(initial_factor=1.1, target_factor=0.1, start_step=0, end_step=None)
+
+    with pytest.raises(ValueError, match='Expected.* 0 <= target_factor'):
+        LinearAnnealingConfig(initial_factor=0.9, target_factor=-0.1, start_step=0, end_step=100)
+
+    with pytest.raises(ValueError, match='Expected.* target_factor < initial_factor'):
+        LinearAnnealingConfig(initial_factor=0.1, target_factor=0.1, start_step=0, end_step=100)
+
+    with pytest.raises(ValueError, match='Expected.* target_factor < initial_factor'):
+        LinearAnnealingConfig(initial_factor=0.1, target_factor=0.2, start_step=0, end_step=100)
+
+    with pytest.raises(ValueError, match='Expected.* start_step >= 0'):
+        LinearAnnealingConfig(initial_factor=1, target_factor=0, start_step=-1, end_step=100)
+
+    with pytest.raises(ValueError, match='Expected.* start_step < end_step'):
+        LinearAnnealingConfig(initial_factor=1, target_factor=0, start_step=100, end_step=100)
+
+    with pytest.raises(ValueError, match='Expected.* start_step < end_step'):
+        LinearAnnealingConfig(initial_factor=1, target_factor=0, start_step=100, end_step=99)