wehub-resource-sync
106 lines
4.1 KiB
C++
106 lines
4.1 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/phi/kernels/uniform_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/common/complex.h"
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#include "paddle/phi/common/type_traits.h"
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#include "paddle/phi/core/generator.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/complex_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void UniformKernel(const Context &dev_ctx,
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const IntArray &shape,
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DataType dtype,
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const Scalar &min,
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const Scalar &max,
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int seed,
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DenseTensor *out) {
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out->Resize(shape.GetData());
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T *data = dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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int64_t real_seed = seed != 0 ? seed : dev_ctx.GetGenerator()->Random64();
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// algo:
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// 0: philox4x32_10_pytorch
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// 1: mt
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// 2: philox4x32_10_curand
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int algo = 0;
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// Handle complex types separately
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if constexpr (std::is_same_v<T, phi::dtype::complex<float>> ||
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std::is_same_v<T, phi::dtype::complex<double>>) {
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using RealType = phi::dtype::Real<T>; // float or double
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using XPUType = typename XPUTypeTrait<RealType>::Type;
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RealType min_val = min.to<RealType>();
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RealType max_val = max.to<RealType>();
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// Generate random values for real and imaginary parts separately
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DenseTensor real_part, imag_part;
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real_part.Resize(out->dims());
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imag_part.Resize(out->dims());
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RealType *real_data = dev_ctx.template Alloc<RealType>(&real_part);
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RealType *imag_data = dev_ctx.template Alloc<RealType>(&imag_part);
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// Generate real part
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int r = xpu::uniform<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<XPUType *>(real_data),
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real_part.numel(),
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static_cast<XPUType>(min_val),
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static_cast<XPUType>(max_val),
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real_seed,
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algo);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
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// Generate imaginary part with different seed
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r = xpu::uniform<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<XPUType *>(imag_data),
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imag_part.numel(),
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static_cast<XPUType>(min_val),
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static_cast<XPUType>(max_val),
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real_seed + 1,
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algo);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
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// Combine real and imaginary parts using ComplexKernel
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ComplexKernel<RealType, Context>(dev_ctx, real_part, imag_part, out);
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} else {
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// Original implementation for non-complex types
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using XPUType = typename XPUTypeTrait<T>::Type;
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int r = xpu::uniform<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<XPUType *>(data),
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out->numel(),
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static_cast<XPUType>(min.to<float>()),
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static_cast<XPUType>(max.to<float>()),
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real_seed,
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algo);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "uniform");
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(uniform,
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XPU,
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ALL_LAYOUT,
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phi::UniformKernel,
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float,
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phi::float16,
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phi::bfloat16,
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phi::complex64) {}
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