Added a test case

Author: cehongwang

tests/py/dynamo/runtime/test_005_dynamic_allocation.py

@@ -0,0 +1,41 @@
+import importlib
+import unittest
+
+import torch
+import torch_tensorrt as torch_trt
+from torch.testing._internal.common_utils import TestCase
+from torch_tensorrt.dynamo.utils import COSINE_THRESHOLD, cosine_similarity
+
+assertions = unittest.TestCase()
+
+if importlib.util.find_spec("torchvision"):
+    import torchvision.models as models
+
+
+class TestDynamicAllocation(TestCase):
+    def test_dynamic_allocation(self):
+        inputs = [torch.rand((100, 3, 224, 224)).to("cuda")]
+
+        settings = {
+            "ir": "dynamo",
+            "use_python_runtime": False,
+            "enabled_precisions": {torch.float32},
+            "immutable_weights": False,
+            "lazy_engine_init": True,
+            "dynamically_allocate_resources": True,
+        }
+
+        model = models.resnet152(pretrained=True).eval().to("cuda")
+        compiled_module = torch_trt.compile(model, inputs=inputs, **settings)
+        compiled_module(*inputs)
+
+        # Inference on PyTorch model
+        model_output = model(*inputs)
+        cos_sim = cosine_similarity(model_output, compiled_module(*inputs))
+        assertions.assertTrue(
+            cos_sim > COSINE_THRESHOLD,
+            msg=f"EfficientNet-B0 TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
+        )
+
+        # Clean up model env
+        torch._dynamo.reset()