提交 c50060bb 编写于 作者: T tensor-tang

add jitcode impl and use it

上级 142bb417
......@@ -26,3 +26,4 @@ USE_JITKERNEL_GEN(kGRUH1)
USE_JITKERNEL_GEN(kGRUHtPart1)
USE_JITKERNEL_GEN(kGRUHtPart2)
USE_JITKERNEL_GEN(kNCHW16CMulNC)
USE_JITKERNEL_GEN(kSeqPool)
/* 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/jit/gen/seqpool.h"
#include "paddle/fluid/operators/jit/registry.h"
#include "paddle/fluid/platform/cpu_info.h"
namespace paddle {
namespace operators {
namespace jit {
namespace gen {
void SeqPoolJitCode::genCode() {
constexpr int block = YMM_FLOAT_BLOCK;
constexpr int max_num_regs = 8;
const int num_block = w_ / block;
const int num_groups = num_block / max_num_regs;
int rest_num_regs = num_block % max_num_regs;
if (type_ == SeqPoolType::kAvg) {
float scalar = 1.f / h_;
mov(reg32_scalar, scalar);
} else if (type_ == SeqPoolType::kSqrt) {
float scalar = 1.f / std::sqrt(static_cast<float>(h_));
mov(reg32_scalar, scalar);
}
// TODO(TJ): make height load from params
const int group_len = max_num_regs * block * sizeof(float);
for (int g = 0; g < num_groups; ++g) {
pool_height<ymm_t>(g * group_len, block, max_num_regs);
}
if (rest_num_regs > 0) {
pool_height<ymm_t>(num_groups * group_len, block, rest_num_regs);
}
// rest part
const int rest = w_ % block;
const bool has_block4 = rest / 4 > 0;
const bool has_block2 = (rest % 4) / 2 > 0;
const bool has_block1 = (rest % 2) == 1;
const int w_offset = num_block * YMM_FLOAT_BLOCK * sizeof(float);
for (int h = 0; h < h_; ++h) {
int offset = h * w_ * sizeof(float) + w_offset;
const int shift_regs = (h == 0) ? 0 : max_num_regs;
int reg_idx = 0;
if (has_block4) {
vmovups(xmm_t(reg_idx + shift_regs), ptr[param1 + offset]);
offset += sizeof(float) * 4;
reg_idx++;
}
if (has_block2) {
vmovq(xmm_t(reg_idx + shift_regs), ptr[param1 + offset]);
offset += sizeof(float) * 2;
reg_idx++;
}
if (has_block1) {
vmovss(xmm_t(reg_idx + shift_regs), ptr[param1 + offset]);
reg_idx++;
}
rest_num_regs = reg_idx;
if (h > 0) {
for (int i = 0; i < reg_idx; ++i) {
vaddps(xmm_t(i), xmm_t(i), xmm_t(i + max_num_regs));
}
}
}
// save right now
int offset = w_offset;
if (type_ == SeqPoolType::kAvg || type_ == SeqPoolType::kSqrt) {
vbroadcastss(xmm_t(max_num_regs - 1), reg32_scalar);
for (int i = 0; i < rest_num_regs; ++i) {
vmulps(xmm_t(i), xmm_t(i), xmm_t(max_num_regs - 1));
}
}
int reg_idx = 0;
if (has_block4) {
vmovups(ptr[param2 + offset], xmm_t(reg_idx));
offset += sizeof(float) * 4;
reg_idx++;
}
if (has_block2) {
vmovq(ptr[param2 + offset], xmm_t(reg_idx));
offset += sizeof(float) * 2;
reg_idx++;
}
if (has_block1) {
vmovss(ptr[param2 + offset], xmm_t(reg_idx));
}
ret();
}
class SeqPoolCreator : public JitCodeCreator<seq_pool_attr_t> {
public:
bool UseMe(const seq_pool_attr_t& attr) const override {
return platform::MayIUse(platform::avx);
}
size_t CodeSize(const seq_pool_attr_t& attr) const override {
// TODO(TJ): remove attr.h when enabled height
bool yes =
attr.type == SeqPoolType::kAvg || attr.type == SeqPoolType::kSqrt;
return 96 /* basic */ +
((attr.w / YMM_FLOAT_BLOCK + 4 /* rest */) * 2 /* for sum */
* (attr.h + (yes ? 3 : 1 /*for avg or sqrt*/))) *
8;
}
std::unique_ptr<GenBase> CreateJitCode(
const seq_pool_attr_t& attr) const override {
PADDLE_ENFORCE_GT(attr.w, 0);
PADDLE_ENFORCE_GT(attr.h, 0);
return make_unique<SeqPoolJitCode>(attr, CodeSize(attr));
}
};
} // namespace gen
} // namespace jit
} // namespace operators
} // namespace paddle
namespace gen = paddle::operators::jit::gen;
REGISTER_JITKERNEL_GEN(kSeqPool, gen::SeqPoolCreator);
/* 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. */
#pragma once
#include <string>
#include "glog/logging.h"
#include "paddle/fluid/operators/jit/gen/jitcode.h"
namespace paddle {
namespace operators {
namespace jit {
namespace gen {
class SeqPoolJitCode : public JitCode {
public:
explicit SeqPoolJitCode(const seq_pool_attr_t& attr,
size_t code_size = 256 * 1024,
void* code_ptr = nullptr)
: JitCode(code_size, code_ptr), h_(attr.h), w_(attr.w), type_(attr.type) {
if (type_ != SeqPoolType::kSum) {
LOG(FATAL) << "Only support sum pool yet ";
}
this->genCode();
}
virtual const char* name() const {
std::string base = "SeqPoolJitCode";
if (type_ == SeqPoolType::kSum) {
base += "_Sum";
} else if (type_ == SeqPoolType::kAvg) {
base += "_Avg";
} else if (type_ == SeqPoolType::kSqrt) {
base += "_Sqrt";
}
base += ("_W" + std::to_string(w_));
// TODO(TJ): make h load from params
base += ("_H" + std::to_string(h_));
return base.c_str();
}
void genCode() override;
protected:
template <typename JMM>
void pool_height(int w_offset, int block, int max_num_regs) {
for (int h = 0; h < h_; ++h) {
int offset = h * w_ * sizeof(float) + w_offset;
const int shift_regs = (h == 0) ? 0 : max_num_regs;
for (int i = 0; i < max_num_regs; ++i) {
vmovups(JMM(i + shift_regs), ptr[param1 + offset]);
offset += sizeof(float) * block;
}
if (h > 0) {
// sum anyway
for (int i = 0; i < max_num_regs; ++i) {
vaddps(JMM(i), JMM(i), JMM(i + max_num_regs));
}
}
}
// save right now
if (type_ == SeqPoolType::kAvg || type_ == SeqPoolType::kSqrt) {
vbroadcastss(JMM(max_num_regs), reg32_scalar);
}
int offset = w_offset;
for (int i = 0; i < max_num_regs; ++i) {
if (type_ == SeqPoolType::kAvg || type_ == SeqPoolType::kSqrt) {
vmulps(JMM(i), JMM(i), JMM(max_num_regs));
}
vmovups(ptr[param2 + offset], JMM(i));
offset += sizeof(float) * block;
}
}
private:
int h_;
int w_;
SeqPoolType type_;
reg64_t param1{abi_param1};
reg64_t param2{abi_param2};
reg64_t param3{abi_param3};
reg32_t reg32_scalar{r8d};
};
} // namespace gen
} // namespace jit
} // namespace operators
} // namespace paddle
......@@ -44,8 +44,11 @@ size_t JitCodeKey<gru_attr_t>(const gru_attr_t& attr) {
template <>
size_t JitCodeKey<seq_pool_attr_t>(const seq_pool_attr_t& attr) {
size_t key = static_cast<size_t>(attr.type);
return key + (attr.w << act_type_shift);
size_t key = attr.w;
// TODO(TJ): support height, then removed it from key
constexpr int w_shift = 30;
return (key << act_type_shift) + static_cast<int>(attr.type) +
(static_cast<size_t>(attr.h) << (act_type_shift + w_shift));
}
} // namespace jit
......
......@@ -255,11 +255,11 @@ class SequencePoolFunctor<platform::CPUDeviceContext, T> {
jit::seq_pool_attr_t attr;
attr.w = input.numel() / input.dims()[0];
attr.type = jit::SeqPoolType::kSum;
auto seqpool =
jit::Get<jit::kSeqPool, jit::SeqPoolTuples<T>, platform::CPUPlace>(
attr);
for (int i = 0; i < static_cast<int>(lod.size()) - 1; ++i) {
attr.h = static_cast<int>(lod[i + 1] - lod[i]);
auto seqpool =
jit::Get<jit::kSeqPool, jit::SeqPoolTuples<T>, platform::CPUPlace>(
attr);
seqpool(src, dst, &attr);
dst += attr.w;
src += attr.h * attr.w;
......
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