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Update BlockMomentumDistributedLearner.h #3501

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Update BlockMomentumDistributedLearner.h #3501

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4f79190
Update BlockMomentumDistributedLearner.h
Aghagolzadeh Nov 9, 2018
17a02f4
Update BlockMomentumDistributedLearner.h
Aghagolzadeh Nov 9, 2018
3e6eef5
Update BlockMomentumDistributedLearner.h
Aghagolzadeh Nov 9, 2018
54f8f14
Update DistributedCommunicator.cpp
Aghagolzadeh Nov 12, 2018
4a620e7
Fix DumpNode crash
rpengms Nov 16, 2018
c298985
Update progress_print.py
Aghagolzadeh Nov 19, 2018
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18 changes: 10 additions & 8 deletions Source/1BitSGD/BlockMomentumDistributedLearner.h
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Original file line number Diff line number Diff line change
Expand Up @@ -524,38 +524,40 @@ namespace CNTK
ResetBuffer<double>(i, p);
else if (p->GetDataType() == DataType::Float)
ResetBuffer<float>(i, p);
else if (p->GetDataType() == DataType::Float16)
ResetBuffer<half, float16>(i, p);
else
RuntimeError("Unsupported type.");
}
}

template<class ElemType>
template<class ElemTypeV1, class ElemTypeV2=ElemTypeV1>
void ResetBuffer(size_t index, const NDArrayViewPtr& p)
{
auto data = p->GetMatrix<ElemType>();
auto data = p->GetMatrix<ElemTypeV1>();
if (!m_blockLevelSmoothedGradient[index])
{
// has not been initialized yet
auto pSmoothedGrad = std::make_shared<NDArrayView>(AsDataType<ElemType>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
pSmoothedGrad->SetValue(static_cast<ElemType>(0));
auto pSmoothedGrad = std::make_shared<NDArrayView>(AsDataType<ElemTypeV2>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
pSmoothedGrad->SetValue(static_cast<ElemTypeV2>(0));
m_blockLevelSmoothedGradient[index] = pSmoothedGrad;
}

if (!m_prevParameters[index])
{
NDArrayViewPtr newValue = std::make_shared<NDArrayView>(AsDataType<ElemType>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
std::shared_ptr<Matrix<ElemType>> newData = newValue->GetWritableMatrix<ElemType>();
NDArrayViewPtr newValue = std::make_shared<NDArrayView>(AsDataType<ElemTypeV2>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
std::shared_ptr<Matrix<ElemTypeV1>> newData = newValue->GetWritableMatrix<ElemTypeV1>();
newData->SetValue(*data);
m_prevParameters[index] = newValue;
}
else
{
m_prevParameters[index]->GetWritableMatrix<ElemType>()->SetValue(*data);
m_prevParameters[index]->GetWritableMatrix<ElemTypeV1>()->SetValue(*data);
}

if (!m_tempBlockGradient[index])
{
m_tempBlockGradient[index] = std::make_shared<NDArrayView>(AsDataType<ElemType>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
m_tempBlockGradient[index] = std::make_shared<NDArrayView>(AsDataType<ElemTypeV2>(), p->Shape(), AsDeviceDescriptor(data->GetDeviceId()));
}
}

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2 changes: 2 additions & 0 deletions Source/CNTKv2LibraryDll/DistributedCommunicator.cpp
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Expand Up @@ -14,6 +14,7 @@
#include "GPUDataTransferer.h"
#include <numeric>
#include "Utils.h"
#include<iostream>

using namespace Microsoft::MSR::CNTK;

Expand Down Expand Up @@ -732,6 +733,7 @@ namespace CNTK
{
if (m_nccl->IsSupported() && !dataOnCPU)
{
std::cerr << " NCCL fp16 allreduce" << endl;
m_nccl->AllReduce(inputData, outputData, numElements, op);

return;
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3 changes: 2 additions & 1 deletion Source/Common/Include/Sequences.h
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Expand Up @@ -546,7 +546,8 @@ struct MBLayout
LogicError("GetColumnIndex: t out of sequence bounds.");
if (seq.s > GetNumParallelSequences())
LogicError("GetColumnIndex: seq.s out of sequence bounds."); // can only happen if 'seq' does not come out of our own m_sequences array, which is verboten
ptrdiff_t tIn = (ptrdiff_t)t + seq.tBegin; // shifted time index
//ptrdiff_t tIn = (ptrdiff_t)t + seq.tBegin; // shifted time index
ptrdiff_t tIn = (ptrdiff_t)t + (seq.tBegin > 0 ? seq.tBegin : 0 ); // shifted time index
if (tIn < 0 || (size_t)tIn >= GetNumTimeSteps())
LogicError("GetColumnIndex: Attempted to access a time step that is accessing a portion of a sequence that is not included in current minibatch."); // we may encounter this for truncated BPTT
size_t col = (size_t)tIn * GetNumParallelSequences() + seq.s;
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2 changes: 2 additions & 0 deletions bindings/python/cntk/logging/progress_print.py
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Expand Up @@ -220,6 +220,8 @@ def write(self, key, value):
def ___logprint(self, logline):
if self.log_to_file == None:
# to stdout. if distributed, all ranks merge output into stdout
t = time.localtime()
print(str(t.tm_year) + '-' + str(t.tm_mon) + '-' + str(t.tm_mday) + ' ' + str(t.tm_hour) + ':' + str(t.tm_min) + ':' + str(t.tm_sec), end = ' ')
print(logline)
else:
# to named file. if distributed, one file per rank
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