wehub-resource-sync
119 lines
4.3 KiB
C++
119 lines
4.3 KiB
C++
// 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/autotune/cache.h"
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#include <iomanip>
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#include "glog/logging.h"
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namespace phi::autotune {
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size_t TransposeKey(const std::vector<int64_t>& x_dims,
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const std::vector<int32_t>& perm,
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DataType dtype) {
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const auto rank = perm.size();
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return GenKey(x_dims, perm, rank, static_cast<int>(dtype));
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}
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std::string AlgorithmTypeString(int64_t algo_type) {
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if (algo_type == static_cast<int64_t>(AlgorithmType::kConvForward)) {
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return "conv_forward";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kConvBackwardData)) {
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return "conv_backward_data";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kConvBackwardFilter)) {
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return "conv_backward_filter";
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}
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#ifdef PADDLE_WITH_CUDNN_FRONTEND
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if (algo_type == static_cast<int64_t>(AlgorithmType::kConvForwardV8)) {
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return "conv_forward_v8";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kConvBackwardDataV8)) {
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return "conv_backward_data_v8";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kConvBackwardFilterV8)) {
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return "conv_backward_filter_v8";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kScaleBiasReluConvBNstats)) {
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return "scale_bias_relu_conv_bnstats";
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} else if (algo_type == static_cast<int64_t>(AlgorithmType::kBNFinalize)) {
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return "bn_finalize";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kScaleBiasAddRelu)) {
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return "scale_bias_add_relu";
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} else if (algo_type ==
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static_cast<int64_t>(AlgorithmType::kDgradDreluBnBwdWeight)) {
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return "dgrad_drelu_bnbwdweight";
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} else if (algo_type == static_cast<int64_t>(AlgorithmType::kDbnApply)) {
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return "dbn_apply";
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} else if (algo_type == static_cast<int64_t>(AlgorithmType::kBnActWgrad)) {
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return "bn_act_wgrad";
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}
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#endif
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return std::to_string(algo_type);
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}
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void AutoTuneCache::UpdateStatus() {
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int64_t size = 0;
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int64_t cache_hits = 0;
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int64_t cache_misses = 0;
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int name_width = 24;
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std::cout.setf(std::ios::left);
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for (auto& v : auto_tune_map_) {
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VLOG(4) << "AlgoType: " << std::setfill(' ') << std::setw(name_width)
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<< AlgorithmTypeString(v.first)
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<< " Cache Size: " << v.second.Size()
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<< " Hits: " << v.second.CacheHits()
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<< " Misses: " << v.second.CacheMisses()
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<< " Hit Rate: " << v.second.CacheHitRate();
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size += v.second.Size();
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cache_hits += v.second.CacheHits();
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cache_misses += v.second.CacheMisses();
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}
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for (auto& v : conv_auto_tune_map_) {
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VLOG(4) << "AlgoType: " << std::setfill(' ') << std::setw(name_width)
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<< AlgorithmTypeString(v.first)
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<< " Cache Size: " << v.second.Size()
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<< " Hits: " << v.second.CacheHits()
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<< " Misses: " << v.second.CacheMisses()
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<< " Hit Rate: " << v.second.CacheHitRate();
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size += v.second.Size();
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cache_hits += v.second.CacheHits();
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cache_misses += v.second.CacheMisses();
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}
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#ifdef PADDLE_WITH_CUDNN_FRONTEND
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for (auto& v : cudnn_v8_auto_tune_map_) {
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VLOG(4) << "AlgoType: " << std::setfill(' ') << std::setw(name_width)
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<< AlgorithmTypeString(v.first)
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<< " Cache Size: " << v.second.Size()
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<< " Hits: " << v.second.CacheHits()
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<< " Misses: " << v.second.CacheMisses()
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<< " Hit Rate: " << v.second.CacheHitRate();
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size += v.second.Size();
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cache_hits += v.second.CacheHits();
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cache_misses += v.second.CacheMisses();
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}
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#endif
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total_size_ = size;
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total_cache_hits_ = cache_hits;
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total_cache_misses_ = cache_misses;
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}
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} // namespace phi::autotune
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