feat: support aten.scalar_tensor dynamo converter

Author: zewenli98

py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py

@@ -2626,3 +2626,20 @@ def aten_ops_pdist(
         args[0],
         args_bounds_check(args, 1, 2),
     )
+
+
+@dynamo_tensorrt_converter(torch.ops.aten.scalar_tensor.default)
+def aten_ops_scalar_tensor(
+    ctx: ConversionContext,
+    target: Target,
+    args: Tuple[Argument, ...],
+    kwargs: Dict[str, Argument],
+    name: str,
+) -> Union[TRTTensor, Sequence[TRTTensor]]:
+    return impl.unary.scalar_tensor(
+        ctx,
+        target,
+        SourceIR.ATEN,
+        name,
+        args[0],
+    )

py/torch_tensorrt/dynamo/conversion/impl/unary/ops.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Optional, Union
 
 import tensorrt as trt
 import torch_tensorrt.dynamo.conversion.impl as impl
@@ -10,6 +10,7 @@
     get_trt_tensor,
 )
 from torch_tensorrt.dynamo.conversion.impl.unary.base import convert_unary
+from torch_tensorrt.fx.converters.converter_utils import set_layer_name
 from torch_tensorrt.fx.types import TRTTensor
 
 
@@ -459,3 +460,16 @@ def trunc(
     return impl.elementwise.trunc_div(
         ctx, target, source_ir, f"{name}_trunc", input_val, dividend
     )
+
+
+def scalar_tensor(
+    ctx: ConversionContext,
+    target: Target,
+    source_ir: Optional[SourceIR],
+    name: str,
+    scalar: Union[int, float, bool],
+) -> TRTTensor:
+    tensor = get_trt_tensor(ctx, scalar, f"{name}_scalar_tensor")
+    identity_layer = ctx.net.add_identity(tensor)
+    set_layer_name(identity_layer, target, name, source_ir)
+    return identity_layer.get_output(0)

tests/py/dynamo/conversion/test_scalar_tensor_aten.py

@@ -0,0 +1,69 @@
+import torch
+import torch.nn as nn
+from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
+
+from .harness import DispatchTestCase
+
+
+class TestScalarTensorConverter(DispatchTestCase):
+    @parameterized.expand(
+        [
+            (-2.00001,),
+            (-1.3,),
+            (-0.0,),
+            (1.0,),
+            (2.99,),
+        ]
+    )
+    def test_scalar_tensor_float(self, scalar):
+        class ScalarTensor(nn.Module):
+            def forward(self):
+                return torch.ops.aten.scalar_tensor.default(scalar)
+
+        inputs = []
+        self.run_test(
+            ScalarTensor(),
+            inputs,
+        )
+
+    @parameterized.expand(
+        [
+            (-9999,),
+            (-1,),
+            (0,),
+            (2,),
+            (99999,),
+        ]
+    )
+    def test_scalar_tensor_int(self, scalar):
+        class ScalarTensor(nn.Module):
+            def forward(self):
+                return torch.ops.aten.scalar_tensor.default(scalar)
+
+        inputs = []
+        self.run_test(
+            ScalarTensor(),
+            inputs,
+        )
+
+    @parameterized.expand(
+        [
+            (True,),
+            (False,),
+        ]
+    )
+    def test_scalar_tensor_bool(self, scalar):
+        class ScalarTensor(nn.Module):
+            def forward(self):
+                return torch.ops.aten.scalar_tensor.default(scalar)
+
+        inputs = []
+        self.run_test(
+            ScalarTensor(),
+            inputs,
+        )
+
+
+if __name__ == "__main__":
+    run_tests()