Update SpectralOps.cpp

Author: Wetitpig

src/ATen/native/xpu/mkl/SpectralOps.cpp

@@ -373,90 +373,6 @@ Tensor& _fft_c2c_mkl_out(
   return out;
 }
 
-Tensor _fft_r2c_mkl(
-  const Tensor& self,
-  IntArrayRef dim,
-  int64_t normalization,
-  bool onesided) {
-if (dim.empty()) {
-  return self.clone();
-}
-
-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 sorted_dims = impl::_sort_dims(self, dim, /*exclude_last=*/true);
-auto out = at::empty(
-    out_sizes, self.options().dtype(c10::toComplexType(self.scalar_type())));
-
-{
-  auto working_tensor = self;
-  while (!sorted_dims.empty()) {
-    const auto max_dims =
-        std::min(static_cast<size_t>(impl::mkl_max_ndim), sorted_dims.size());
-    auto fft_dims = IntArrayRef(sorted_dims)
-                        .slice(sorted_dims.size() - max_dims, max_dims);
-    impl::_exec_fft(
-        out,
-        working_tensor,
-        out_sizes,
-        fft_dims,
-        onesided,
-        /*forward=*/true);
-    sorted_dims.resize(sorted_dims.size() - max_dims);
-
-    if (sorted_dims.empty()) {
-      break;
-    }
-
-    sorted_dims = impl::_sort_dims(self, sorted_dims);
-
-    if (working_tensor.is_same(self)) {
-      working_tensor = std::move(out);
-      out = at::empty(
-          out_sizes,
-          self.options().dtype(c10::toComplexType(self.scalar_type())));
-    } else {
-      std::swap(out, working_tensor);
-    }
-  }
-}
-
-// Only need to normalize the onesided slice since data in the other half is
-// overwritten
-out = impl::_fft_apply_normalization(out, normalization, input_sizes, dim);
-auto working_tensor = self;
-if (!onesided) {
-  if (out.size(last_dim) != out_sizes[last_dim]) {
-    working_tensor.resize_(out_sizes, MemoryFormat::Contiguous);
-    working_tensor.slice(last_dim, 0, last_dim_halfsize).copy_(out);
-    out = std::move(working_tensor);
-  }
-  _fft_fill_with_conjugate_symmetry_(out, dim);
-}
-
-return out;
-}
-
-Tensor& _fft_r2c_mkl_out(
-  const Tensor& self,
-  IntArrayRef dim,
-  int64_t normalization,
-  bool onesided,
-  Tensor& out) {
-auto result = _fft_r2c_mkl(
-    self, dim, static_cast<int64_t>(fft_norm_mode::none), onesided);
-at::native::resize_output(out, result.sizes());
-out.copy_(result);
-return out;
-}
-
 void HermitSymmImpl(Tensor& input, int64_t dim, int pos) {
   std::vector<at::indexing::TensorIndex> indices(
       input.dim(), at::indexing::Slice());