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Bg/fix bn solvers is applicable #3355

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merged 16 commits into from
Nov 2, 2024
Merged

Bg/fix bn solvers is applicable #3355

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382bd23
fix driver for old ocl kernel
bghimireamd Oct 30, 2024
b4e1a00
fix template name
bghimireamd Oct 30, 2024
14f1a1f
fix review comments
bghimireamd Oct 31, 2024
6a5cc92
fix isApplicable for CK and OCL bn spatial
bghimireamd Nov 1, 2024
749cde2
bring change from bharriso/bn-ocl-bf16
bghimireamd Nov 2, 2024
0242120
fix gtest issue in bn for ck and ocl
bghimireamd Nov 2, 2024
185b7ec
fix minor issue
bghimireamd Nov 2, 2024
f852441
Merge branch 'bharriso/bn-ocl-bf16' of github.com:ROCm/MIOpen into bg…
bghimireamd Nov 2, 2024
e34c18f
fix clang format
bghimireamd Nov 2, 2024
e9f7092
hip tidy
bghimireamd Nov 2, 2024
45741cc
fix gtest sample and fix hiptidy
bghimireamd Nov 2, 2024
a648b71
* move type check logic to problem description of batch norm
bghimireamd Nov 2, 2024
bed3d9a
fix network cache
bghimireamd Nov 2, 2024
743cb9e
fix minor testing issue
bghimireamd Nov 2, 2024
e1bb0c1
disable ck bn for now
bghimireamd Nov 2, 2024
23e8695
Merge branch 'bharriso/bn-ocl-bf16' into bg/fix_bn_solvers_is_applicable
BrianHarrisonAMD Nov 2, 2024
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41 changes: 28 additions & 13 deletions src/batch_norm_api.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,10 @@ namespace miopen {
namespace debug {

void LogCmdBNorm(const miopenTensorDescriptor_t xDesc,
const miopenTensorDescriptor_t sMeanDesc,
const miopenTensorDescriptor_t yDesc,
const miopenTensorDescriptor_t scaleDesc,
const miopenTensorDescriptor_t biasDesc,
const miopenTensorDescriptor_t saveMeanDesc,
miopenBatchNormMode_t bn_mode,
const void* resultRunningMean,
const void* resultRunningVariance,
Expand All @@ -61,7 +64,10 @@ void LogCmdBNorm(const miopenTensorDescriptor_t xDesc,
if(miopen::IsLoggingCmd())
{
const std::string& str = BnormArgsForMIOpenDriver(xDesc,
sMeanDesc,
yDesc,
scaleDesc,
biasDesc,
saveMeanDesc,
bn_mode,
resultRunningMean,
resultRunningVariance,
Expand Down Expand Up @@ -206,7 +212,7 @@ miopenBatchNormalizationForwardInference_V2(miopenHandle_t handle,
const miopenTensorDescriptor_t yDesc,
void* y,
const miopenTensorDescriptor_t scaleDesc,
const miopenTensorDescriptor_t BiasDesc,
const miopenTensorDescriptor_t biasDesc,
const miopenTensorDescriptor_t estMeanDesc,
const miopenTensorDescriptor_t estVarianceDesc,
void* bnScale,
Expand All @@ -222,7 +228,7 @@ miopenBatchNormalizationForwardInference_V2(miopenHandle_t handle,
yDesc,
y,
scaleDesc,
BiasDesc,
biasDesc,
estMeanDesc,
estVarianceDesc,
bnScale,
Expand All @@ -232,12 +238,15 @@ miopenBatchNormalizationForwardInference_V2(miopenHandle_t handle,
epsilon);

miopen::debug::LogCmdBNorm(xDesc,
yDesc,
scaleDesc,
biasDesc,
estMeanDesc,
bn_mode,
estimatedMean,
estimatedVariance,
nullptr,
nullptr,
estMeanDesc,
estimatedVariance,
miopen::debug::BatchNormDirection_t::ForwardInference);

// In case of NxCxDxHxW
Expand All @@ -256,7 +265,7 @@ miopenBatchNormalizationForwardInference_V2(miopenHandle_t handle,
: miopen::deref(yDesc),
DataCast(y),
miopen::deref(scaleDesc),
miopen::deref(BiasDesc),
miopen::deref(biasDesc),
miopen::deref(estMeanDesc),
miopen::deref(estVarianceDesc),
DataCast(bnScale),
Expand All @@ -277,7 +286,7 @@ miopenBatchNormalizationForwardTraining_V2(miopenHandle_t handle,
const miopenTensorDescriptor_t yDesc,
void* y,
const miopenTensorDescriptor_t scaleDesc,
const miopenTensorDescriptor_t BiasDesc,
const miopenTensorDescriptor_t biasDesc,
const miopenTensorDescriptor_t savedMeanDesc,
const miopenTensorDescriptor_t savedVarianceDesc,
void* bnScale,
Expand All @@ -296,7 +305,7 @@ miopenBatchNormalizationForwardTraining_V2(miopenHandle_t handle,
yDesc,
y,
scaleDesc,
BiasDesc,
biasDesc,
savedMeanDesc,
savedVarianceDesc,
bnScale,
Expand All @@ -309,6 +318,9 @@ miopenBatchNormalizationForwardTraining_V2(miopenHandle_t handle,
resultSaveInvVariance);

miopen::debug::LogCmdBNorm(xDesc,
yDesc,
scaleDesc,
biasDesc,
savedMeanDesc,
bn_mode,
resultRunningMean,
Expand All @@ -332,7 +344,7 @@ miopenBatchNormalizationForwardTraining_V2(miopenHandle_t handle,
: miopen::deref(yDesc),
DataCast(y),
miopen::deref(scaleDesc),
miopen::deref(BiasDesc),
miopen::deref(biasDesc),
miopen::deref(savedMeanDesc),
miopen::deref(savedVarianceDesc),
DataCast(bnScale),
Expand Down Expand Up @@ -360,7 +372,7 @@ miopenBatchNormalizationBackward_V2(miopenHandle_t handle,
const miopenTensorDescriptor_t dxDesc,
void* dx,
const miopenTensorDescriptor_t scaleDesc,
const miopenTensorDescriptor_t BiasDesc,
const miopenTensorDescriptor_t biasDesc,
const miopenTensorDescriptor_t savedMeanDesc,
const miopenTensorDescriptor_t savedVarianceDesc,
const void* bnScale,
Expand All @@ -379,7 +391,7 @@ miopenBatchNormalizationBackward_V2(miopenHandle_t handle,
dxDesc,
dx,
scaleDesc,
BiasDesc,
biasDesc,
savedMeanDesc,
savedVarianceDesc,
bnScale,
Expand All @@ -389,6 +401,9 @@ miopenBatchNormalizationBackward_V2(miopenHandle_t handle,
savedMean,
savedInvVariance);
miopen::debug::LogCmdBNorm(xDesc,
dyDesc,
scaleDesc,
biasDesc,
savedMeanDesc,
bn_mode,
nullptr,
Expand Down Expand Up @@ -417,7 +432,7 @@ miopenBatchNormalizationBackward_V2(miopenHandle_t handle,
: miopen::deref(dxDesc),
DataCast(dx),
miopen::deref(scaleDesc),
miopen::deref(BiasDesc),
miopen::deref(biasDesc),
miopen::deref(savedMeanDesc),
miopen::deref(savedVarianceDesc),
DataCast(bnScale),
Expand Down
125 changes: 117 additions & 8 deletions src/batchnorm/problem_description.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,109 @@ namespace miopen {

namespace batchnorm {

bool is_fp16_or_bfp16(miopenDataType_t type)
{
return ((type == miopenHalf) || (type == miopenBFloat16));
}

bool is_fp32_or_fp64(miopenDataType_t type)
{
return ((type == miopenFloat) || (type == miopenDouble));
}

bool is_fp32(miopenDataType_t type) { return (type == miopenFloat); }

bool IsOCLInferTypeValid(const ProblemDescription& bn_problem)
{
// case 1 : mix type
return (
(is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetYDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnBias().GetType())) ||
// case 2 : float type
(is_fp32(bn_problem.GetXDesc().GetType()) && is_fp32(bn_problem.GetYDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnBias().GetType())));
}

bool IsCKInferTypeValid(const ProblemDescription& bn_problem)
{
// case 1 : mix type
return ((is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetYDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetBnScale().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetBnBias().GetType()) &&
is_fp32(bn_problem.GetBnSMean().GetType()) &&
is_fp32(bn_problem.GetBnSVar().GetType())) ||
// case 2 : fp32 or fp64
(is_fp32_or_fp64(bn_problem.GetXDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetYDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnScale().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnBias().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSMean().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSVar().GetType())));
}

bool IsOCLFwdTrainTypeValid(const ProblemDescription& bn_problem)
{
// case 1 : mix type
return (
(is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetYDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnBias().GetType())) ||
// case 2 : float type
(is_fp32(bn_problem.GetXDesc().GetType()) && is_fp32(bn_problem.GetYDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnBias().GetType())));
}

bool IsCKFwdTrainTypeValid(const ProblemDescription& bn_problem)
{
// case 1 : mix type
return ((is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetYDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetBnScale().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetBnBias().GetType()) &&
is_fp32(bn_problem.GetBnSMean().GetType()) &&
is_fp32(bn_problem.GetBnSVar().GetType())) ||
// case 2 : fp32 or fp64
(is_fp32_or_fp64(bn_problem.GetXDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetYDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnScale().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnBias().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSMean().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSVar().GetType())));
}

bool IsOCLBwdTypeValid(const ProblemDescription& bn_problem)
{
return (
(is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetDXDesc().GetType()) &&
is_fp16_or_bfp16(bn_problem.GetDYDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnSMean().GetType()) &&
is_fp32(bn_problem.GetBnSVar().GetType())) ||
// case 1 : fp32
(is_fp32(bn_problem.GetXDesc().GetType()) && is_fp32(bn_problem.GetDXDesc().GetType()) &&
is_fp32(bn_problem.GetBnScale().GetType()) && is_fp32(bn_problem.GetBnBias().GetType()) &&
is_fp32(bn_problem.GetBnSMean().GetType()) && is_fp32(bn_problem.GetBnSVar().GetType())));
}

bool IsCKBwdTypeValid(const ProblemDescription& bn_problem)
{
return ((is_fp16_or_bfp16(bn_problem.GetXDesc().GetType()) &&
bn_problem.GetDXDesc().GetType() == miopenFloat &&
is_fp16_or_bfp16(bn_problem.GetBnScale().GetType()) &&
bn_problem.GetDYDesc().GetType() == miopenFloat &&
bn_problem.GetBnSMean().GetType() == miopenFloat &&
bn_problem.GetBnSVar().GetType() == miopenFloat) ||
// case 1 : fp32 or fp64
(is_fp32_or_fp64(bn_problem.GetXDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetDXDesc().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnScale().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnBias().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSMean().GetType()) &&
is_fp32_or_fp64(bn_problem.GetBnSVar().GetType())));
}

NetworkConfig ProblemDescription::MakeNetworkConfig() const
{
switch(direction)
Expand Down Expand Up @@ -67,7 +170,7 @@ NetworkConfig ProblemDescription::MakeForwardTrainingNetworkConfig() const
size_t ygridsize = 1;

bool bfpmixparm = false;
if(xDesc.GetType() == miopenHalf && GetBnScaleBiasMeanVarDesc().GetType() == miopenFloat)
if(IsMix())
{
bfpmixparm = true;
}
Expand Down Expand Up @@ -137,7 +240,7 @@ NetworkConfig ProblemDescription::MakeForwardTrainingNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "c" << c;
}
Expand All @@ -154,7 +257,7 @@ NetworkConfig ProblemDescription::MakeForwardTrainingNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "single" << static_cast<int>(single);
ss << "n" << n;
Expand All @@ -173,7 +276,7 @@ NetworkConfig ProblemDescription::MakeForwardTrainingNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "gx" << xgridsize;
ss << "gy" << ygridsize;
Expand All @@ -187,6 +290,8 @@ NetworkConfig ProblemDescription::MakeForwardTrainingNetworkConfig() const
ss << "hw" << in_cstride;
}
ss << "layout" << in_layout;
ss << "scaleType" << static_cast<int>(IsScaleFp16());
ss << "scaleType" << static_cast<int>(IsScaleFp32());

return NetworkConfig{ss.str()};
}
Expand All @@ -203,12 +308,14 @@ NetworkConfig ProblemDescription::MakeForwardInferenceNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "mode" << bn_mode;
ss << "HWdims" << in_cstride;
ss << "C" << c;
ss << "layout" << in_layout;
ss << "scaleType" << static_cast<int>(IsScaleFp16());
ss << "scaleType" << static_cast<int>(IsScaleFp32());

return NetworkConfig{ss.str()};
}
Expand All @@ -218,7 +325,7 @@ NetworkConfig ProblemDescription::MakeBackwardNetworkConfig() const
std::ostringstream ss;

bool bfpmixparm = false;
if(xDesc.GetType() == miopenHalf && GetScaleBiasDiffDesc().GetType() == miopenFloat)
if(xDesc.GetType() == miopenHalf && GetBnScale().GetType() == miopenFloat)
{
bfpmixparm = true;
}
Expand Down Expand Up @@ -311,7 +418,7 @@ NetworkConfig ProblemDescription::MakeBackwardNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "single" << static_cast<int>(single);
ss << "gcn" << ldsgcn;
Expand All @@ -334,11 +441,13 @@ NetworkConfig ProblemDescription::MakeBackwardNetworkConfig() const
ss << "fp16" << static_cast<int>(IsFp16());
ss << "fp32" << static_cast<int>(IsFp32());
ss << "fp64" << static_cast<int>(IsFp64());
ss << "fbf16" << static_cast<int>(IsBfp16());
ss << "fbf16" << static_cast<int>(IsBFp16());
ss << "fmix" << static_cast<int>(IsMix());
ss << "nhw" << in_nhw;
}
ss << "layout" << in_layout;
ss << "scaleType" << static_cast<int>(IsScaleFp16());
ss << "scaleType" << static_cast<int>(IsScaleFp32());

return NetworkConfig{ss.str()};
}
Expand Down
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