chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/hash_kernel_impl.h

@@ -0,0 +1,58 @@
+// Copyright (c) 2024 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
+
+extern "C" {
+#include <xxhash.h>
+}
+#include <vector>
+
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+#include "paddle/phi/kernels/funcs/hash_utils.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void HashKernel(const Context& dev_ctx,
+                const DenseTensor& x,
+                int num_hash,
+                int64_t mod_by,
+                DenseTensor* out) {
+  auto* out_t = out;
+  auto* in_t = &x;
+
+  auto in_dims = in_t->dims();
+
+  std::vector<int64_t> out_dims;
+  funcs::HashOutputSize(in_dims, out_dims, num_hash);
+  out_t->Resize(out_dims);
+  auto* output = dev_ctx.template Alloc<T>(out_t);
+
+  auto seq_length = in_dims[0];
+  auto last_dim = in_dims[in_dims.size() - 1];
+  auto* input = in_t->data<T>();
+  for (int idx = 0; idx < seq_length; ++idx) {
+    for (int ihash = 0; ihash != num_hash; ++ihash) {
+      output[idx * num_hash + ihash] =
+          XXH64(input, sizeof(T) * last_dim, ihash) % mod_by;
+    }
+    input += last_dim;
+  }
+
+  out_t->set_lod(in_t->lod());
+}
+
+}  // namespace phi