diff --git a/aten/src/ATen/native/mps/operations/FastFourierTransform.mm b/aten/src/ATen/native/mps/operations/FastFourierTransform.mm
index 9a208e814cf..9f50a2343a4 100644
--- a/aten/src/ATen/native/mps/operations/FastFourierTransform.mm
+++ b/aten/src/ATen/native/mps/operations/FastFourierTransform.mm
@@ -1,3 +1,5 @@
+#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
+#include <ATen/native/Resize.h>
 #include <ATen/native/SpectralOpsUtils.h>
 #include <ATen/native/mps/OperationUtils.h>
 
@@ -37,25 +39,12 @@ NSArray<NSNumber*>* IntArrayToNSArray(IntArrayRef arr) {
 } // anonymous namespace
 
 Tensor _fft_c2r_mps(const Tensor& self, IntArrayRef dim, int64_t normalization, int64_t last_dim_size) {
-  TORCH_CHECK(self.is_complex());
-  auto in_sizes = self.sizes();
-  DimVector out_sizes(in_sizes.begin(), in_sizes.end());
-  out_sizes[dim.back()] = last_dim_size;
-  auto out = at::empty(out_sizes, self.options().dtype(c10::toRealValueType(self.scalar_type())));
+  auto out = at::empty({}, self.options().dtype(c10::toRealValueType(self.scalar_type())));
   return _fft_c2r_mps_out(self, dim, normalization, last_dim_size, out);
 }
 
 Tensor _fft_r2c_mps(const Tensor& self, IntArrayRef dim, int64_t normalization, bool onesided) {
-  TORCH_CHECK(self.is_floating_point());
-  auto input_sizes = self.sizes();
-  DimVector out_sizes(input_sizes.begin(), input_sizes.end());
-  auto last_dim = dim.back();
-  auto last_dim_halfsize = (input_sizes[last_dim]) / 2 + 1;
-  if (onesided) {
-    out_sizes[last_dim] = last_dim_halfsize;
-  }
-
-  auto out = at::empty(out_sizes, self.options().dtype(c10::toComplexType(self.scalar_type())));
+  auto out = at::empty({}, self.options().dtype(c10::toComplexType(self.scalar_type())));
   return _fft_r2c_mps_out(self, dim, normalization, onesided, out);
 }
 
@@ -72,6 +61,17 @@ using namespace mps;
 
 // TODO: Investigate numerical discrepancies see https://github.com/pytorch/pytorch/issues/120237
 Tensor& _fft_r2c_mps_out(const Tensor& self, IntArrayRef dim, int64_t normalization, bool onesided, Tensor& out) {
+  TORCH_CHECK(self.scalar_type() == kFloat || self.scalar_type() == kHalf, "Only float and half dtypes are supported");
+  TORCH_CHECK(out.scalar_type() == c10::toComplexType(self.scalar_type()));
+  const auto input_sizes = self.sym_sizes();
+  SymDimVector out_sizes(input_sizes.begin(), input_sizes.end());
+  auto last_dim = dim.back();
+  auto last_dim_halfsize = (input_sizes[last_dim]) / 2 + 1;
+  if (onesided) {
+    out_sizes[last_dim] = last_dim_halfsize;
+  }
+  at::native::resize_output_symint(out, out_sizes);
+
   auto key = __func__ + getTensorsStringKey({self, out}) + ":" + getArrayRefString(dim) + ":" +
       std::to_string(normalization) + ":" + std::to_string(onesided);
   @autoreleasepool {
@@ -112,6 +112,12 @@ Tensor& _fft_c2r_mps_out(const Tensor& self,
                          int64_t normalization,
                          int64_t last_dim_size,
                          Tensor& out) {
+  TORCH_CHECK(self.is_complex(), "Input must be complex");
+  TORCH_CHECK(out.scalar_type() == c10::toRealValueType(self.scalar_type()), "Unexpected output type");
+  const auto in_sizes = self.sym_sizes();
+  SymDimVector out_sizes(in_sizes.begin(), in_sizes.end());
+  out_sizes[dim.back()] = last_dim_size;
+  at::native::resize_output_symint(out, out_sizes);
   auto key = __func__ + getTensorsStringKey({self}) + ":" + getArrayRefString(dim) + ":" +
       std::to_string(normalization) + ":" + std::to_string(last_dim_size);
   @autoreleasepool {