Register operators, remove unused operator

aten/src/ATen/native/mkldnn/xpu/Blas.cpp

@@ -3,7 +3,8 @@
 #include "BlasImpl.h"
 
 namespace at {
-namespace native::xpu {
+namespace native {
+namespace xpu {
 
 using namespace impl;
 
@@ -362,120 +363,6 @@ Tensor& addmv_out(
   return out;
 }
 
-Tensor& addmv_(
-    Tensor& self,
-    const Tensor& mat,
-    const Tensor& vec,
-    at::Scalar beta,
-    at::Scalar alpha) {
-  Tensor self_v;
-  TORCH_CHECK(
-      (mat.dim() == 2 && vec.dim() == 1 && self.dim() <= 1),
-      "vector + matrix @ vector expected, got ",
-      self.dim(),
-      ", ",
-      mat.dim(),
-      ", ",
-      vec.dim());
-  if (self.dim() == 1 && self.size(0) != 1) {
-    TORCH_CHECK(
-        (mat.size(1) == vec.size(0) && mat.size(0) == self.size(0)),
-        "size mismatch, get ",
-        self.size(0),
-        ", ",
-        mat.size(0),
-        "x",
-        mat.size(1),
-        ",",
-        vec.size(0));
-    self_v = self.view({self.size(0), 1});
-  } else {
-    TORCH_CHECK(
-        (mat.size(1) == vec.size(0)),
-        "size mismatch, get ",
-        mat.size(0),
-        "x",
-        mat.size(1),
-        ",",
-        vec.size(0));
-    self_v = self;
-  }
-
-  Tensor vec_v = vec.view({vec.size(0), 1});
-  self_v.addmm_(mat, vec_v, beta, alpha);
-  return self;
-}
-
-Tensor tensordot(
-    const Tensor& input1,
-    const Tensor& input2,
-    IntArrayRef dims1,
-    IntArrayRef dims2) {
-  TORCH_CHECK(
-      dims1.size() == dims2.size(),
-      "both dimension lists should have same length");
-  int64_t csize = 1; // total size of the contracted dimensions
-  Tensor t1 = input1;
-  Tensor t2 = input2;
-  for (const auto i : c10::irange(dims1.size())) {
-    int s1 = input1.size(dims1[i]);
-    int s2 = input2.size(dims2[i]);
-    if (s2 == 1) { // broadcasted dimensions can be summed right away
-      t1 = t1.sum(dims1[i], true);
-    } else if (s1 == 1) {
-      t2 = t2.sum(dims2[i], true);
-    } else {
-      TORCH_CHECK(
-          s1 == s2,
-          "contracted dimensions need to match, but first has size ",
-          s1,
-          " in dim ",
-          dims1[i],
-          " and second has size ",
-          s2,
-          " in dim ",
-          dims2[i]);
-      csize *= s1;
-    }
-  }
-  auto cdims1 = at::dim_list_to_bitset(dims1, input1.dim());
-  auto cdims2 = at::dim_list_to_bitset(dims2, input2.dim());
-  std::vector<int64_t> p1, p2,
-      rsizes; // p1, p2: input permutations, rsizes: sizes of the result
-  p1.reserve(input1.dim());
-  p2.reserve(input2.dim());
-  rsizes.reserve(input1.dim() + input2.dim() - (int64_t)dims1.size());
-  int64_t size1 = 1; // number of non-contracted elements in input1
-  int64_t size2 = 1; // number of non-contracted elements in input2
-
-  // fill the permutations and compute sizes
-  for (const auto i : c10::irange(input1.dim())) {
-    if (!cdims1[i]) {
-      p1.emplace_back(i);
-      size1 *= t1.size(i);
-      rsizes.emplace_back(t1.size(i));
-    }
-  }
-  for (const auto x : dims1) {
-    p1.emplace_back(x);
-  }
-  for (const auto x : dims2) {
-    p2.emplace_back(x);
-  }
-  for (const auto i : c10::irange(input2.dim())) {
-    if (!cdims2[i]) {
-      p2.emplace_back(i);
-      size2 *= t2.size(i);
-      rsizes.emplace_back(t2.size(i));
-    }
-  }
-  // permut and reshape for matrix multiplication
-  t1 = t1.permute(p1).reshape({size1, csize});
-  t2 = t2.permute(p2).reshape({csize, size2});
-  // multiply and reshape to target size
-  return at::mm(t1, t2).reshape(rsizes);
-}
-
 Tensor& tensordot_out(
     const Tensor& input1,
     const Tensor& input2,
@@ -512,5 +399,24 @@ Tensor& tensordot_out(
   return result;
 }
 
-} // namespace native::xpu
+
+} // namespace xpu
+
+TORCH_LIBRARY_IMPL(aten, XPU, m){
+  m.impl("admm.out", TORCH_FN(addmm_out));
+  m.impl("_addmm_activation.out", TORCH_FN(_addmm_activation_out));
+  m.impl("mm.out", TORCH_FN(mm_out));
+  m.impl("mm", TORCH_FN(mm));
+  m.impl("baddbmm.out", TORCH_FN(baddbmm_out));
+  m.impl("baddbmm_", TORCH_FN(baddbmm_));
+  m.impl("baddbmm", TORCH_FN(baddbmm));
+  m.impl("addbmm.out", TORCH_FN(addbmm_out));
+  m.impl("addbmm_", TORCH_FN(addbmm_));
+  m.impl("addbmm", TORCH_FN(addbmm));
+  m.impl("bmm.out", TORCH_FN(bmm_out));
+  m.impl("bmm", TORCH_FN(bmm));
+  m.impl("addmv.out", TORCH_FN(addmv_out));
+  m.impl("tensordot.out", TORCH_FN(tensordot_out));
+}
+} // namespace native
 } // namespace at