diff --git a/onnxscript/function_libs/torch_lib/ops/fft.py b/onnxscript/function_libs/torch_lib/ops/fft.py
index ea92dc347d..037f69feb4 100644
--- a/onnxscript/function_libs/torch_lib/ops/fft.py
+++ b/onnxscript/function_libs/torch_lib/ops/fft.py
@@ -14,7 +14,7 @@
 
 from typing import Optional, Sequence
 
-from onnxscript import INT64
+from onnxscript import INT64, ir
 from onnxscript.function_libs.torch_lib.registration import torch_op
 from onnxscript.function_libs.torch_lib.tensor_typing import TFloat
 from onnxscript.onnx_opset import opset18 as op
@@ -118,12 +118,18 @@ def aten__fft_c2r(
     # Torch truncates/pads on the last dimension only. Typically, the only valid values that can be passed
     # into PyTorch are n or n//2+1, where n is self.shape[dim[-1]], but this is not always the case, so we
     # place no such restriction on the ONNX side.
-    transformed = op.DFT(
-        transformed,
-        dft_length=last_dim_size,
-        axis=dimension,
-        inverse=True,
-        onesided=False,
+    scale = (op.CastLike(last_dim_size, self)) / op.CastLike(
+        op.Shape(transformed, start=dimension, end=dimension + 1), self
+    )
+    transformed = (
+        op.DFT(
+            transformed,
+            dft_length=last_dim_size,
+            axis=dimension,
+            inverse=True,
+            onesided=False,
+        )
+        * scale
     )
     transformed = _fftn_onnx_normalization(
         transformed,