chore: import upstream snapshot with attribution

paddle/phi/kernels/linear_v2_kernel.h

@@ -0,0 +1,53 @@
+// 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.
+#pragma once
+
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/enforce.h"
+
+namespace phi {
+
+// we don't receive 2+d tensor as weight
+inline std::tuple<int64_t, int64_t, int64_t> canonicalize_dims(
+    const DenseTensor& input,
+    const DenseTensor& weight,
+    const bool transpose_weight) {
+  const auto input_dims = input.dims();
+  const auto weight_dims = weight.dims();
+  // We assume weight to be [K, N] if not tranasposed, [N, K] if transposed, [K]
+  // if 1D
+  const int64_t N = weight_dims.size() < 2 ? 1 : weight_dims[!transpose_weight];
+  const int64_t K =
+      weight_dims.size() < 2 ? weight_dims[0] : weight_dims[transpose_weight];
+
+  int64_t M = input_dims.size() >= 2 ? input_dims[input_dims.size() - 2] : 1;
+  if (input_dims.size() > 2) {
+    // Accumulate the batch dims for input
+    for (int64_t i = 0; i < input_dims.size() - 2; ++i) {
+      M *= input_dims[i];
+    }
+  }
+
+  return {M, N, K};
+}
+
+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);
+}  // namespace phi