wehub-resource-sync
95 lines
2.5 KiB
Plaintext
95 lines
2.5 KiB
Plaintext
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/trunc_kernel.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/backends/gpu/gpu_info.h"
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#include "paddle/phi/backends/gpu/gpu_launch_config.h"
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#include "paddle/phi/backends/gpu/gpu_primitives.h"
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#include "paddle/phi/common/amp_type_traits.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T>
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class TruncFunctor {
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public:
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__device__ TruncFunctor(const T x) : x_(x) {}
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__device__ T operator()() {
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using MT = typename MPTypeTrait<T>::Type;
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return static_cast<T>(trunc(static_cast<MT>(x_)));
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}
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public:
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const T x_;
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};
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template <>
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class TruncFunctor<int> {
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public:
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__device__ TruncFunctor(const int x) : x_(x) {}
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__device__ int operator()() { return x_; }
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public:
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const int x_;
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};
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template <>
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class TruncFunctor<int64_t> {
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public:
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__device__ TruncFunctor(const int64_t x) : x_(x) {}
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__device__ int64_t operator()() { return x_; }
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public:
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const int64_t x_;
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};
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template <typename T>
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__global__ void Trunc(const T* x, T* out, int64_t N) {
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CUDA_KERNEL_LOOP_TYPE(index, N, int64_t) {
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TruncFunctor<T> functor(x[index]);
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out[index] = functor();
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}
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}
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template <typename T, typename Context>
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void TruncKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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const auto* x_data = x.data<T>();
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auto* out_data = dev_ctx.template Alloc<T>(out);
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if (x.numel() == 0) {
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return;
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}
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int64_t numel = x.numel();
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auto config = backends::gpu::GetGpuLaunchConfig1D(dev_ctx, numel);
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Trunc<<<config.block_per_grid, config.thread_per_block>>>(
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x_data, out_data, numel);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(trunc,
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GPU,
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ALL_LAYOUT,
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phi::TruncKernel,
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float,
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double,
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int,
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int64_t,
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phi::float16,
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phi::bfloat16) {}
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