chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/dot_kernel.cc

@@ -0,0 +1,71 @@
+// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/kernels/dot_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+#include "paddle/phi/kernels/full_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void DotKernel(const Context& dev_ctx,
+               const DenseTensor& x,
+               const DenseTensor& y,
+               DenseTensor* out) {
+  if (x.numel() == 0 || y.numel() == 0) {
+    // x[2, 1], y[2, 0], out[2]
+    Full<T, Context>(dev_ctx, out->dims(), 0, out);
+    return;
+  }
+  if (out->numel() <= 0) {
+    return;
+  }
+  auto const *x_ptr = x.data<T>(), *x_ptr_ = &x_ptr[0];
+  auto const *y_ptr = y.data<T>(), *y_ptr_ = &y_ptr[0];
+  T* z = dev_ctx.template Alloc<T>(out);
+
+  // Loop over the total N elements of both operands while sum-reducing every
+  // B pairs along the way where B is the dimension of the least ordered axis
+  auto&& d = x.dims();
+  auto const N = x.numel();
+
+  // prevent div 0
+  auto const _B = d.size() == 0 ? 1 : d[d.size() - 1];
+  auto const B = _B != 0 ? _B : 1;
+
+  // initialize for N / B <= 0
+  z[0] = 0;
+
+  for (int j = 0; j < N / B; j++) {
+    T ss = 0;
+    for (int i = 0; i < B; i++) ss += (*x_ptr_++) * (*y_ptr_++);
+    z[j] = ss;
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(dot,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::DotKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::complex64,
+                   phi::complex128) {}