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[MXNET-1179] Enforce deterministic algorithms in convolution layers #12992

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Oct 30, 2018
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[MXNET-1179] Enforce deterministic algorithms in convolution layers #12992

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a6164dc
add env variable to choose deterministic cudnn alg
apeforest Oct 26, 2018
2b363ee
Merge remote-tracking branch 'upstream/master' into feature/cudnn_det…
apeforest Oct 26, 2018
3da0f7d
set default value to false
apeforest Oct 29, 2018
69eeedc
Merge remote-tracking branch 'upstream/master' into feature/cudnn_det…
apeforest Oct 29, 2018
65d64d2
fix build failure in Windows GPU
apeforest Oct 29, 2018
7bc1d4d
revert the previous change
apeforest Oct 29, 2018
ca98f5f
only check determinism in CUDNN 7.x release
apeforest Oct 29, 2018
ad3a484
Add cudnn version check
apeforest Oct 29, 2018
2a108ef
fix lint error
apeforest Oct 29, 2018
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4 changes: 4 additions & 0 deletions src/operator/nn/cudnn/cudnn_convolution-inl.h
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Expand Up @@ -889,13 +889,17 @@ class CuDNNConvolutionOp {
size_t workspace_byte, CuDNNAlgo<AlgoType> *algo) {
// Determine the fastest acceptable algo that matches the algo_preference (-1 = any),
// regardless of mathType.
bool enforce_determinism = dmlc::GetEnv("MXNET_ENFORCE_DETERMINISM", false);
for (decltype(perf_results.size()) i = 0; i != perf_results.size(); ++i) {
const auto &result = perf_results[i];
bool algo_is_tensor_core = false;
#if CUDNN_MAJOR >= 7
algo_is_tensor_core = result.mathType == CUDNN_TENSOR_OP_MATH;
#endif
if (result.status == CUDNN_STATUS_SUCCESS &&
#if CUDNN_MAJOR >= 7
(!enforce_determinism || result.determinism == cudnnDeterminism_t::CUDNN_DETERMINISTIC) &&
#endif
(param_.cudnn_tune.value() != conv::kLimited || result.memory <= workspace_byte)) {
algo->Set(result.algo, algo_is_tensor_core);
return;
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4 changes: 4 additions & 0 deletions src/operator/nn/cudnn/cudnn_deconvolution-inl.h
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Expand Up @@ -829,13 +829,17 @@ class CuDNNDeconvolutionOp {
void AlgoFinalSelect(const std::vector<PerfType> &perf_results, std::string kernel_name,
size_t workspace_byte, CuDNNAlgo<AlgoType> *algo) {
// Determine the fastest acceptable algo regardless of mathType.
bool enforce_determinism = dmlc::GetEnv("MXNET_ENFORCE_DETERMINISM", false);
for (decltype(perf_results.size()) i = 0; i != perf_results.size(); ++i) {
const auto &result = perf_results[i];
bool algo_is_tensor_core = false;
#if CUDNN_MAJOR >= 7
algo_is_tensor_core = result.mathType == CUDNN_TENSOR_OP_MATH;
#endif
if (result.status == CUDNN_STATUS_SUCCESS &&
#if CUDNN_MAJOR >= 7
(!enforce_determinism || result.determinism == cudnnDeterminism_t::CUDNN_DETERMINISTIC) &&
#endif
(param_.cudnn_tune.value() != conv::kLimited || result.memory <= workspace_byte)) {
algo->Set(result.algo, algo_is_tensor_core);
return;
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5 changes: 5 additions & 0 deletions src/operator/nn/cudnn/cudnn_pooling-inl.h
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Expand Up @@ -48,7 +48,12 @@ class CuDNNPoolingOp {
param_ = p;
switch (param_.pool_type) {
case pool_enum::kMaxPooling:
#if CUDNN_MAJOR >= 7
mode_ = dmlc::GetEnv("MXNET_ENFORCE_DETERMINISM", false) ?
CUDNN_POOLING_MAX_DETERMINISTIC : CUDNN_POOLING_MAX;
#else
mode_ = CUDNN_POOLING_MAX;
#endif
break;
case pool_enum::kAvgPooling:
if (param_.count_include_pad.has_value() && !param_.count_include_pad.value()) {
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