Fix grid_sample

py/torch_tensorrt/dynamo/conversion/impl/grid.py

@@ -4,13 +4,13 @@
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
-from torch_tensorrt.fx.converters.converter_utils import set_layer_name
-from torch_tensorrt.fx.types import TRTTensor
+from torch_tensorrt.dynamo.conversion.converter_utils import set_layer_name
+from torch_tensorrt.dynamo.types import TRTTensor
 
-# nearest, linear, cubic
+# bilinear, nearest, bicubic
 GridSamplerInterpolationMode = {
-    0: trt.InterpolationMode.NEAREST,
-    1: trt.InterpolationMode.LINEAR,
+    0: trt.InterpolationMode.LINEAR,
+    1: trt.InterpolationMode.NEAREST,
     2: trt.InterpolationMode.CUBIC,
 }
 

py/torch_tensorrt/dynamo/lowering/_decompositions.py

@@ -566,6 +566,15 @@ def scaled_dot_product_cudnn_attention_decomposition(
     return attn, None, None, None, 0, 0, None, None, None
 
 
+@register_torch_trt_decomposition(
+    aten.cudnn_grid_sampler, registry=TORCH_TRT_DECOMPOSITIONS
+)
+def cudnn_grid_sampler_decomposition(
+    x: torch.Tensor, grid: torch.Tensor
+) -> torch.Tensor:
+    return torch.grid_sampler_2d(x, grid, 0, 0, True)
+
+
 def get_decompositions(
     enable_experimental_decompositions: bool = False,
 ) -> Dict[OpOverload, Callable[[Any], Any]]:

tests/py/dynamo/lowering/test_decompositions.py

@@ -2117,6 +2117,56 @@ def forward(self, query, key, value, attn_bias=None):
             msg="Scaled_dot_product_cudnn_attention TRT outputs don't match with the original model.",
         )
 
+    def test_lowering_cudnn_grid_sampler(self):
+        class TestModule(torch.nn.Module):
+            def forward(self, x, grid):
+                return torch.ops.aten.cudnn_grid_sampler.default(x, grid)
+
+        # Operations expected to be removed in the traced graph after decompositions
+        expected_ops = {torch.ops.aten.grid_sampler_2d.default}
+        unexpected_ops = {torch.ops.aten.cudnn_grid_sampler.default}
+
+        inputs = [
+            torch.randn(1, 3, 5, 7, device="cuda"),
+            torch.randn(1, 5, 7, 2, device="cuda"),
+        ]
+
+        exported_program = torch.export.export(TestModule(), tuple(inputs))
+        fx_graph = exported_program.module()
+        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.assertEqual(
+            len(unexpected_ops_seen),
+            0,
+            f"The following unexpected ops were encountered: {unexpected_ops_seen}",
+        )
+
+        self.assertEqual(
+            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
+        trt_model = torch_tensorrt.dynamo.compile(
+            exported_program, inputs, min_block_size=1
+        )
+        torch.testing.assert_close(
+            trt_model(*inputs),
+            fx_graph(*inputs),
+            rtol=RTOL,
+            atol=ATOL,
+            msg="Cudnn_grid_sampler TRT outputs don't match with the original model.",
+        )
+
 
 if __name__ == "__main__":
     run_tests()