Added more tests

@@ -372,6 +372,44 @@ def test_resnet18_dynamic(ir):
 )
 
 
+@pytest.mark.unit
+def test_resnet18_dynamic_torch_exec_ops(ir):
+"""
+This tests export save and load functionality on Resnet18 model
+"""
+model = models.resnet18().eval().cuda()
+input = torch.randn((1, 3, 224, 224)).to("cuda")
+
+compile_spec = {
+"inputs": [
+torchtrt.Input(
+min_shape=(1, 3, 224, 224),
+opt_shape=(4, 3, 224, 224),
+max_shape=(8, 3, 224, 224),
+dtype=torch.float32,
+name="x",
+)
+],
+"ir": ir,
+"min_block_size": 1,
+"cache_built_engines": False,
+"reuse_cached_engines": False,
+"torch_executed_ops": {torch.ops.aten.addmm, "torch.ops.aten.add"},
+}
+
+exp_program = torchtrt.dynamo.trace(model, **compile_spec)
+trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+torchtrt.save(trt_module, trt_ep_path)
+deser_trt_module = torchtrt.load(trt_ep_path).module()
+outputs_pyt = deser_trt_module(input)
+outputs_trt = trt_module(input)
+cos_sim = cosine_similarity(outputs_pyt, outputs_trt[0])
+assertions.assertTrue(
+cos_sim > COSINE_THRESHOLD,
+msg=f"test_resnet18 TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
+)
+
+
 @pytest.mark.unit
 def test_hybrid_conv_fallback(ir):
 """