fix: Add decomposition for aten.addmm

py/torch_tensorrt/dynamo/backend/lowering/_decompositions.py

@@ -56,5 +56,14 @@ def alias_replacement(x: torch.Tensor) -> torch.Tensor:
     return x
 
 
+@register_decomposition(torch.ops.aten.addmm, registry=DECOMPOSITIONS)
+def addmm_replacement(
+    input_: torch.Tensor, mat1: torch.Tensor, mat2: torch.Tensor, *, beta=1, alpha=1
+) -> torch.Tensor:
+    return torch.add(
+        torch.mul(input_, beta), torch.mul(torch.matmul(mat1, mat2), alpha)
+    )
+
+
 def get_decompositions():
     return DECOMPOSITIONS

py/torch_tensorrt/dynamo/backend/test/test_lowering.py → py/torch_tensorrt/dynamo/backend/test/test_decompositions.py

@@ -2,6 +2,8 @@
 from utils import lower_graph_testing
 from torch.testing._internal.common_utils import run_tests, TestCase
 import torch
+from torch_tensorrt.dynamo import compile
+from torch_tensorrt.dynamo.common_utils.test_utils import DECIMALS_OF_AGREEMENT
 
 
 class TestLowering(TestCase):
@@ -109,6 +111,74 @@ def forward(self, x):
             f"The following expected ops were not encountered: {expected_ops_unseen}",
         )
 
+    def test_lowering_addmm(self):
+        class AddMM(torch.nn.Module):
+            def forward(self, x, y, z):
+                return torch.addmm(x, y, z, beta=16, alpha=5)
+
+        # Operations expected to be included in the traced graph after decompositions
+        expected_ops = {
+            torch.ops.aten.add.Tensor,
+            torch.ops.aten.mul.Tensor,
+            torch.ops.aten.mm.default,
+        }
+        unexpected_ops = {torch.ops.aten.addmm.default}
+
+        inputs = [
+            torch.rand(
+                1,
+                1,
+            ).cuda(),
+            torch.rand(
+                7,
+                8,
+            ).cuda(),
+            torch.rand(
+                8,
+                9,
+            ).cuda(),
+        ]
+
+        fx_graph = torch.fx.symbolic_trace(AddMM())
+        unexpected_ops_seen, expected_ops_unseen = lower_graph_testing(
+            fx_graph,
+            inputs,
+            expected_ops=expected_ops,
+            unexpected_ops=unexpected_ops,
+            min_block_size=1,
+        )
+
+        self.assertEquals(
+            len(unexpected_ops_seen),
+            0,
+            f"The following unexpected ops were encountered: {unexpected_ops_seen}",
+        )
+
+        self.assertEquals(
+            len(expected_ops_unseen),
+            0,
+            f"The following expected ops were not encountered: {expected_ops_unseen}",
+        )
+
+        torch._dynamo.reset()
+
+        # Validate that the results between Torch and Torch-TRT are similar
+        optimized_model = compile(
+            fx_graph, inputs, min_block_size=1, pass_through_build_failures=True
+        )
+        optimized_model_results = optimized_model(*inputs).detach().cpu()
+        torch_model_results = fx_graph(*inputs).detach().cpu()
+
+        max_diff = float(
+            torch.max(torch.abs(optimized_model_results - torch_model_results))
+        )
+        self.assertAlmostEqual(
+            max_diff,
+            0,
+            DECIMALS_OF_AGREEMENT,
+            f"AddMM TRT outputs don't match with the original model.",
+        )
+
 
 if __name__ == "__main__":
     run_tests()

py/torch_tensorrt/dynamo/common_utils/test_utils.py

@@ -1,6 +1,7 @@
 import torch
 
 COSINE_THRESHOLD = 0.99
+DECIMALS_OF_AGREEMENT = 5
 
 
 def cosine_similarity(gt_tensor, pred_tensor):