chore: import upstream snapshot with attribution

paddle/phi/kernels/xpu/uniform_kernel.cc

@@ -0,0 +1,105 @@
+/* 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/uniform_kernel.h"
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/common/complex.h"
+#include "paddle/phi/common/type_traits.h"
+#include "paddle/phi/core/generator.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/complex_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void UniformKernel(const Context &dev_ctx,
+                   const IntArray &shape,
+                   DataType dtype,
+                   const Scalar &min,
+                   const Scalar &max,
+                   int seed,
+                   DenseTensor *out) {
+  out->Resize(shape.GetData());
+  T *data = dev_ctx.template Alloc<T>(out);
+  if (out->numel() == 0) {
+    return;
+  }
+
+  int64_t real_seed = seed != 0 ? seed : dev_ctx.GetGenerator()->Random64();
+  // algo:
+  //       0: philox4x32_10_pytorch
+  //       1: mt
+  //       2: philox4x32_10_curand
+  int algo = 0;
+
+  // Handle complex types separately
+  if constexpr (std::is_same_v<T, phi::dtype::complex<float>> ||
+                std::is_same_v<T, phi::dtype::complex<double>>) {
+    using RealType = phi::dtype::Real<T>;  // float or double
+    using XPUType = typename XPUTypeTrait<RealType>::Type;
+    RealType min_val = min.to<RealType>();
+    RealType max_val = max.to<RealType>();
+
+    // Generate random values for real and imaginary parts separately
+    DenseTensor real_part, imag_part;
+    real_part.Resize(out->dims());
+    imag_part.Resize(out->dims());
+    RealType *real_data = dev_ctx.template Alloc<RealType>(&real_part);
+    RealType *imag_data = dev_ctx.template Alloc<RealType>(&imag_part);
+
+    // Generate real part
+    int r = xpu::uniform<XPUType>(dev_ctx.x_context(),
+                                  reinterpret_cast<XPUType *>(real_data),
+                                  real_part.numel(),
+                                  static_cast<XPUType>(min_val),
+                                  static_cast<XPUType>(max_val),
+                                  real_seed,
+                                  algo);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
+
+    // Generate imaginary part with different seed
+    r = xpu::uniform<XPUType>(dev_ctx.x_context(),
+                              reinterpret_cast<XPUType *>(imag_data),
+                              imag_part.numel(),
+                              static_cast<XPUType>(min_val),
+                              static_cast<XPUType>(max_val),
+                              real_seed + 1,
+                              algo);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
+
+    // Combine real and imaginary parts using ComplexKernel
+    ComplexKernel<RealType, Context>(dev_ctx, real_part, imag_part, out);
+  } else {
+    // Original implementation for non-complex types
+    using XPUType = typename XPUTypeTrait<T>::Type;
+    int r = xpu::uniform<XPUType>(dev_ctx.x_context(),
+                                  reinterpret_cast<XPUType *>(data),
+                                  out->numel(),
+                                  static_cast<XPUType>(min.to<float>()),
+                                  static_cast<XPUType>(max.to<float>()),
+                                  real_seed,
+                                  algo);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
+  }
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(uniform,
+                   XPU,
+                   ALL_LAYOUT,
+                   phi::UniformKernel,
+                   float,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::complex64) {}