jit_kernel.cc 2.9 KB
Newer Older
T
tensor-tang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
/* Copyright (c) 2018 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/fluid/operators/math/jit_kernel.h"
T
tensor-tang 已提交
16
#include <functional>
T
tensor-tang 已提交
17
#include <string>
T
tensor-tang 已提交
18 19
#include "paddle/fluid/operators/math/cpu_vec.h"
#include "paddle/fluid/platform/cpu_info.h"
T
tensor-tang 已提交
20 21 22 23 24 25 26 27 28 29 30

namespace paddle {
namespace operators {
namespace math {
namespace jitkernel {

KernelPool& KernelPool::Instance() {
  static KernelPool g_jit_kernels;
  return g_jit_kernels;
}

T
tensor-tang 已提交
31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
template <>
LSTMKernel<float>::LSTMKernel(int d, const std::string& act_gate_str,
                              const std::string& act_cand_str,
                              const std::string& act_cell_str)
    : Kernel(), d_(d) {
  if (platform::jit::MayIUse(platform::jit::avx512_common)) {
    math::VecActivations<float, platform::jit::avx512_common> act_functor;
    act_gate_ = act_functor(act_gate_str);
    act_cell_ = act_functor(act_cell_str);
    act_cand_ = act_functor(act_cand_str);
  } else if (platform::jit::MayIUse(platform::jit::avx2)) {
    math::VecActivations<float, platform::jit::avx2> act_functor;
    act_gate_ = act_functor(act_gate_str);
    act_cell_ = act_functor(act_cell_str);
    act_cand_ = act_functor(act_cand_str);
  } else if (platform::jit::MayIUse(platform::jit::avx)) {
    math::VecActivations<float, platform::jit::avx> act_functor;
    act_gate_ = act_functor(act_gate_str);
    act_cell_ = act_functor(act_cell_str);
    act_cand_ = act_functor(act_cand_str);
  } else {
    math::VecActivations<float, platform::jit::isa_any> act_functor;
    act_gate_ = act_functor(act_gate_str);
    act_cell_ = act_functor(act_cell_str);
    act_cand_ = act_functor(act_cand_str);
  }
}

T
tensor-tang 已提交
59 60 61 62 63 64
template <>
const std::shared_ptr<LSTMKernel<float>>
KernelPool::Get<LSTMKernel<float>, int, const std::string&, const std::string&,
                const std::string&>(int d, const std::string& act_gate,
                                    const std::string& act_cand,
                                    const std::string& act_cell) {
T
tensor-tang 已提交
65 66 67 68 69 70 71 72
  std::string key = "f" + std::to_string(d) + act_gate + act_cand + act_cell;
  if (kers_.find(key) == kers_.end()) {
    auto p =
        std::make_shared<LSTMKernel<float>>(d, act_gate, act_cand, act_cell);
    kers_.insert({key, std::dynamic_pointer_cast<Kernel>(p)});
    return p;
  }
  return std::dynamic_pointer_cast<LSTMKernel<float>>(kers_.at(key));
T
tensor-tang 已提交
73 74 75 76 77 78
}

}  // namespace jitkernel
}  // namespace math
}  // namespace operators
}  // namespace paddle