wehub-resource-sync
105 lines
3.8 KiB
Plaintext
105 lines
3.8 KiB
Plaintext
// Copyright (c) 2023 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/fusion/gpu/fusion_group_kernel.h"
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#include "glog/logging.h"
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#include "paddle/phi/backends/device_code.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/utils/data_type.h"
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namespace phi {
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namespace fusion {
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template <typename Context>
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static void MutableMultiTypeData(std::vector<DenseTensor*>* var,
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const std::vector<int>& data_type,
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const Context& dev_ctx) {
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for (size_t i = 0; i < var->size(); i++) {
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DataType dtype = TransToPhiDataType(data_type[i]);
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if (dtype == DataType::FLOAT32) {
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dev_ctx.template Alloc<float>((*var)[i],
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(*var)[i]->numel() * sizeof(float));
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} else if (dtype == DataType::FLOAT16) {
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dev_ctx.template Alloc<float16>((*var)[i],
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(*var)[i]->numel() * sizeof(float16));
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} else if (dtype == DataType::FLOAT64) {
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dev_ctx.template Alloc<double>((*var)[i],
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(*var)[i]->numel() * sizeof(double));
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}
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}
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}
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template <typename T, typename Context>
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void FusionGroupKernel(const Context& dev_ctx,
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const std::vector<const DenseTensor*>& ins,
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const std::vector<int>& outs_dtype,
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const std::vector<int>& inputs_dtype,
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const std::string& func_name,
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int type,
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std::vector<DenseTensor*> outs) {
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size_t num_ins = ins.size();
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size_t num_outs = outs.size();
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MutableMultiTypeData(&outs, outs_dtype, dev_ctx);
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phi::DeviceCode* dev_code =
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phi::DeviceCodePool::Instance().Get(dev_ctx.GetPlace(), func_name);
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VLOG(3) << "func_name: " << func_name;
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if (type == 0) {
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size_t n = ins[0]->numel();
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std::vector<void*> args;
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args.push_back(&n);
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std::vector<const void*> ptrs(num_ins + num_outs);
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for (size_t i = 0; i < num_ins; ++i) {
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DataType input_dtype = TransToPhiDataType(inputs_dtype[i]);
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if (input_dtype == DataType::FLOAT16) {
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ptrs[i] = ins[i]->data<float16>();
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} else if (input_dtype == DataType::FLOAT32) {
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ptrs[i] = ins[i]->data<float>();
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} else if (input_dtype == DataType::FLOAT64) {
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ptrs[i] = ins[i]->data<double>();
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}
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args.push_back(&ptrs[i]);
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}
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for (size_t j = 0; j < num_outs; ++j) {
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DataType out_dtype = TransToPhiDataType(outs_dtype[j]);
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if (out_dtype == DataType::FLOAT16) {
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ptrs[num_ins + j] = outs[j]->data<float16>();
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} else if (out_dtype == DataType::FLOAT32) {
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ptrs[num_ins + j] = outs[j]->data<float>();
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} else if (out_dtype == DataType::FLOAT64) {
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ptrs[num_ins + j] = outs[j]->data<double>();
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}
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args.push_back(&ptrs[num_ins + j]);
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}
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dev_code->Launch(n, &args);
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}
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}
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} // namespace fusion
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} // namespace phi
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PD_REGISTER_KERNEL(fusion_group,
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GPU,
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ALL_LAYOUT,
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phi::fusion::FusionGroupKernel,
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float,
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double,
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phi::float16) {
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kernel->OutputAt(0).SetDataType(phi::DataType::UNDEFINED);
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}
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