Merge pull request #14284 from PaddlePaddle/revert-14043-conv_cudnn_cache
Revert " Exhaustive search for cuDNN conv."revert-14324-fix_vlog
Xin Pan
7 years ago
committed by
GitHub
commit
0953cd3e16
File diff suppressed because it is too large
Load Diff
@ -1,90 +0,0 @@
|
|||||||
/* Copyright (c) 2016 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 <functional>
|
|
||||||
#include <unordered_map>
|
|
||||||
#include <vector>
|
|
||||||
|
|
||||||
namespace paddle {
|
|
||||||
namespace operators {
|
|
||||||
|
|
||||||
template <typename TAlgorithm>
|
|
||||||
class AlgorithmsCache {
|
|
||||||
public:
|
|
||||||
// Caches the best algorithm for a given
|
|
||||||
// combination of tensor dimensions & compute data type.
|
|
||||||
TAlgorithm GetAlgorithm(
|
|
||||||
const std::vector<int64_t>& dims1, const std::vector<int64_t>& dims2,
|
|
||||||
const std::vector<int>& strides, const std::vector<int>& paddings,
|
|
||||||
const std::vector<int>& dilations,
|
|
||||||
int algorithmFlags, // can set for different data type
|
|
||||||
std::function<TAlgorithm()> gen_func);
|
|
||||||
|
|
||||||
private:
|
|
||||||
std::unordered_map<int64_t, TAlgorithm> hash_;
|
|
||||||
std::mutex mutex_;
|
|
||||||
};
|
|
||||||
|
|
||||||
template <typename TAlgorithm>
|
|
||||||
TAlgorithm AlgorithmsCache<TAlgorithm>::GetAlgorithm(
|
|
||||||
const std::vector<int64_t>& dims1, const std::vector<int64_t>& dims2,
|
|
||||||
const std::vector<int>& strides, const std::vector<int>& paddings,
|
|
||||||
const std::vector<int>& dilations, int algorithmFlags,
|
|
||||||
std::function<TAlgorithm()> gen_func) {
|
|
||||||
std::lock_guard<std::mutex> lock(mutex_);
|
|
||||||
int64_t seed = 0;
|
|
||||||
// Hash all of the inputs, use to try and look up a previously
|
|
||||||
// discovered algorithm, or fall back to generating a new one.
|
|
||||||
std::hash<int64_t> hashFn;
|
|
||||||
// do hash like boost
|
|
||||||
// https://stackoverflow.com/questions/2590677/how-do-i-combine-hash-values-in-c0x
|
|
||||||
for (const auto num : dims1) {
|
|
||||||
seed ^= hashFn(num) + 0x9e3779b9 + (seed << 6) + (seed >> 2);
|
|
||||||
}
|
|
||||||
|
|
||||||
for (const auto num : dims2) {
|
|
||||||
seed ^= hashFn(num) + 0x9e3779b9 + (seed << 6) + (seed >> 2) + 1;
|
|
||||||
}
|
|
||||||
|
|
||||||
for (const auto num : strides) {
|
|
||||||
seed ^= hashFn(static_cast<int64_t>(num)) + 0x9e3779b9 + (seed << 6) +
|
|
||||||
(seed >> 2) + 2;
|
|
||||||
}
|
|
||||||
|
|
||||||
for (const auto num : paddings) {
|
|
||||||
seed ^= hashFn(static_cast<int64_t>(num)) + 0x9e3779b9 + (seed << 6) +
|
|
||||||
(seed >> 2) + 3;
|
|
||||||
}
|
|
||||||
|
|
||||||
for (const auto num : dilations) {
|
|
||||||
seed ^= hashFn(static_cast<int64_t>(num)) + 0x9e3779b9 + (seed << 6) +
|
|
||||||
(seed >> 2) + 4;
|
|
||||||
}
|
|
||||||
|
|
||||||
seed ^= hashFn(static_cast<int64_t>(algorithmFlags)) + 0x9e3779b9 +
|
|
||||||
(seed << 6) + (seed >> 2) + 5;
|
|
||||||
|
|
||||||
if (seed == 0) return gen_func();
|
|
||||||
|
|
||||||
if (hash_.find(seed) == hash_.end()) {
|
|
||||||
TAlgorithm value = gen_func();
|
|
||||||
hash_[seed] = value;
|
|
||||||
}
|
|
||||||
return hash_[seed];
|
|
||||||
}
|
|
||||||
|
|
||||||
} // namespace operators
|
|
||||||
} // namespace paddle
|
|
||||||
Loading…
Reference in new issue