chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/linear_v2_kernel.cc

@@ -0,0 +1,68 @@
+// Copyright (c) 2025 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 <algorithm>
+#include <mutex>
+#include <unordered_map>
+#include "glog/logging.h"
+#include "paddle/phi/common/data_type.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+
+#include "paddle/common/enforce.h"
+#include "paddle/phi/kernels/addmm_kernel.h"
+#include "paddle/phi/kernels/elementwise_add_kernel.h"
+#include "paddle/phi/kernels/impl/matmul_kernel_impl.h"
+#include "paddle/phi/kernels/linear_v2_kernel.h"
+#include "paddle/phi/kernels/reshape_kernel.h"
+#include "paddle/phi/kernels/tile_kernel.h"
+
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/enforce.h"
+#include "paddle/phi/core/scope_guard.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LinearV2Kernel(const Context& dev_ctx,
+                    const DenseTensor& input,
+                    const DenseTensor& weight,
+                    const DenseTensor& bias,
+                    const bool transpose_weight,
+                    DenseTensor* out) {
+  dev_ctx.template Alloc<T>(out);
+  if (out->numel() == 0) {
+    return;
+  }
+
+  // When in CPU, we use legacy linear_logic by default.
+  // TODO(Pan Zhaowu): Adding more efficient kernel for CPU.
+  std::vector<std::int64_t> input_dims_vec = vectorize(input.dims());
+  std::vector<std::int64_t> weight_dims_vec = vectorize(weight.dims());
+
+  MatMulFunction<Context, T>(dev_ctx,
+                             input,
+                             weight,
+                             input_dims_vec,
+                             weight_dims_vec,
+                             out,
+                             false,
+                             transpose_weight);
+  AddKernel<T, Context>(dev_ctx, *out, bias, out);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    linear_v2, CPU, ALL_LAYOUT, phi::LinearV2Kernel, float, double) {}