Create edge_model_compression_test.py

edge_ai/edge_model_compression_test.py

@@ -0,0 +1,24 @@
+import unittest
+import torch
+from edge_ai import load_model, model_quantization, model_pruning, model_knowledge_distillation
+
+class TestEdgeModelCompression(unittest.TestCase):
+    def test_model_quantization(self):
+        model = load_model()
+        model_quantization(model)
+        self.assertTrue(True)
+
+    def test_model_pruning(self):
+        model = load_model()
+        model_pruning(model)
+        self.assertTrue(True)
+
+    def test_model_knowledge_distillation(self):
+        dataset = EdgeAIDataset(np.random.rand(100, 3, 224, 224), np.random.randint(0, 10, 100))
+        teacher = EdgeAIModel()
+        student = EdgeAIModel()
+        model_knowledge_distillation(student, teacher, dataset)
+        self.assertTrue(True)
+
+if __name__ == "__main__":
+    unittest.main()