chore: import upstream snapshot with attribution

2026-07-13 12:40:42 +08:00
commit e25996e7db
15472 changed files with 3536181 additions and 0 deletions
@@ -0,0 +1,69 @@
+// Copyright (c) 2022 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/truncated_gaussian_random_kernel.h"
+
+#include <limits>
+#include <random>
+#include <vector>
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/common/amp_type_traits.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/truncated_normal.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void TruncatedGaussianRandomKernel(const Context& dev_ctx,
+                                   const std::vector<int>& shape,
+                                   float mean,
+                                   float std,
+                                   int seed,
+                                   float a,
+                                   float b,
+                                   DataType dtype,
+                                   DenseTensor* out) {
+  auto tensor = out;
+
+  T* data = dev_ctx.template Alloc<T>(tensor);
+
+  using MT = typename MPTypeTrait<T>::Type;
+
+  std::uniform_real_distribution<MT> dist(std::numeric_limits<float>::min(),
+                                          1.0);
+  TruncatedNormal<MT> truncated_normal(mean, std, a, b);
+  int64_t size = tensor->numel();
+
+  std::shared_ptr<std::mt19937_64> engine;
+  if (seed) {
+    engine = std::make_shared<std::mt19937_64>();
+    engine->seed(seed);
+  } else {
+    engine = dev_ctx.GetGenerator()->GetCPUEngine();
+  }
+  for (int64_t i = 0; i < size; ++i) {
+    data[i] = static_cast<T>(truncated_normal(dist(*engine)));
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(truncated_gaussian_random,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::TruncatedGaussianRandomKernel,
+                   float,
+                   double,
+                   phi::bfloat16) {}