Remove upsample_*.vec

Author: HolyWu

py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py

@@ -3019,7 +3019,7 @@ def aten_ops_pad(
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_nearest1d_default(
+def aten_ops_upsample_nearest1d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3045,7 +3045,7 @@ def aten_ops_upsample_nearest1d_default(
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_nearest2d_default(
+def aten_ops_upsample_nearest2d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3071,7 +3071,7 @@ def aten_ops_upsample_nearest2d_default(
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_nearest3d_default(
+def aten_ops_upsample_nearest3d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3091,41 +3091,13 @@ def aten_ops_upsample_nearest3d_default(
     )
 
 
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_nearest1d.vec)
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_nearest2d.vec)
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_nearest3d.vec)
-@enforce_tensor_types(
-    {
-        0: (TRTTensor,),
-    }
-)
-def aten_ops_upsample_nearest_vec(
-    ctx: ConversionContext,
-    target: Target,
-    args: Tuple[Argument, ...],
-    kwargs: Dict[str, Argument],
-    name: str,
-) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.upsample.upsample(
-        ctx,
-        target,
-        SourceIR.ATEN,
-        name,
-        args[0],
-        size=args_bounds_check(args, 1),
-        scale_factor=args_bounds_check(args, 2),
-        mode="nearest",
-        align_corners=False,
-    )
-
-
 @dynamo_tensorrt_converter(torch.ops.aten.upsample_linear1d.default)
 @enforce_tensor_types(
     {
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_linear1d_default(
+def aten_ops_upsample_linear1d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3151,7 +3123,7 @@ def aten_ops_upsample_linear1d_default(
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_bilinear2d_default(
+def aten_ops_upsample_bilinear2d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3177,7 +3149,7 @@ def aten_ops_upsample_bilinear2d_default(
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_trilinear3d_default(
+def aten_ops_upsample_trilinear3d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3197,41 +3169,13 @@ def aten_ops_upsample_trilinear3d_default(
     )
 
 
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_linear1d.vec)
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_bilinear2d.vec)
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_trilinear3d.vec)
-@enforce_tensor_types(
-    {
-        0: (TRTTensor,),
-    }
-)
-def aten_ops_upsample_linear_vec(
-    ctx: ConversionContext,
-    target: Target,
-    args: Tuple[Argument, ...],
-    kwargs: Dict[str, Argument],
-    name: str,
-) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.upsample.upsample(
-        ctx,
-        target,
-        SourceIR.ATEN,
-        name,
-        args[0],
-        size=args_bounds_check(args, 1),
-        scale_factor=args_bounds_check(args, 3),
-        mode="linear",
-        align_corners=args[2],
-    )
-
-
 @dynamo_tensorrt_converter(torch.ops.aten.upsample_bicubic2d.default)
 @enforce_tensor_types(
     {
         0: (TRTTensor,),
     }
 )
-def aten_ops_upsample_bicubic_default(
+def aten_ops_upsample_bicubic2d(
     ctx: ConversionContext,
     target: Target,
     args: Tuple[Argument, ...],
@@ -3251,32 +3195,6 @@ def aten_ops_upsample_bicubic_default(
     )
 
 
-@dynamo_tensorrt_converter(torch.ops.aten.upsample_bicubic2d.vec)
-@enforce_tensor_types(
-    {
-        0: (TRTTensor,),
-    }
-)
-def aten_ops_upsample_bicubic_vec(
-    ctx: ConversionContext,
-    target: Target,
-    args: Tuple[Argument, ...],
-    kwargs: Dict[str, Argument],
-    name: str,
-) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.upsample.upsample(
-        ctx,
-        target,
-        SourceIR.ATEN,
-        name,
-        args[0],
-        size=args_bounds_check(args, 1),
-        scale_factor=args_bounds_check(args, 3),
-        mode="bicubic",
-        align_corners=args[2],
-    )
-
-
 @dynamo_tensorrt_converter(
     torch.ops.aten.topk.default, capability_validator=topk_validator
 )