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uttInfoInMinibatch->clear();
uttInfoInMinibatch->resize(uttInfo.size());
for (size_t i = 0; i < uttInfo.size(); ++i)
{
size_t startFrameIndexInMinibatch = 0;
size_t numFrames = 0;
for (size_t j = 0; j < pMBLayout->GetNumTimeSteps(); ++j)
{
/* if (pMBLayout->Is(i, j, MinibatchPackingFlags::NoLabel))
{
continue;
}*/
FrameRange fr(pMBLayout, j);
if (pMBLayout->IsGap(fr.Sequence(i)))
{
continue;
}
numFrames += 1;
if (pMBLayout->IsBeyondStartOrEnd(fr.WithTimeOffset((ptrdiff_t) 1).Sequence(i)) || j == pMBLayout->GetNumTimeSteps() - 1)
{
size_t uttIndex = (*uttInfoInMinibatch)[i].size();
wstring uttID = uttInfo[i][uttIndex].first;
(*uttInfoInMinibatch)[i].push_back(
make_pair(uttID, make_pair(startFrameIndexInMinibatch,
numFrames)));
startFrameIndexInMinibatch = j + 1;
numFrames = 0;
}
}
assert(uttInfo[i].size() == (*uttInfoInMinibatch)[i].size());
}
}
// Suppose we have a, b, c 3 streams, the <logLikelihoodIn> is the in the
// following format:
// 1: a11 b11 c11 a12 b12 c12...
// 2: a21 b21 c21 a22 b22 c22...
// 3: a31 b31 c31 a32 b32 c32...
template <class ElemType>
bool UtteranceDerivativeBuffer<ElemType>::SetLikelihood(
const std::vector<std::vector<std::pair<wstring, size_t>>>& uttInfo,
const Matrix<ElemType>& logLikelihoodIn,
const MBLayoutPtr pMBLayout)
{
assert(m_needLikelihood == true);
assert(m_epochEnd == false);
if (m_dimension == 0)
{
m_dimension = logLikelihoodIn.GetNumRows();
}
assert(m_dimension == logLikelihoodIn.GetNumRows());
std::vector<std::vector<
std::pair<wstring, std::pair<size_t, size_t>>>> uttInfoInMinibatch;
ProcessUttInfo(uttInfo, pMBLayout, &uttInfoInMinibatch);
// Checks if we need to move data to CPU.
Matrix<ElemType> logLikelihood = logLikelihoodIn.DeepClone();
if (logLikelihood.GetDeviceId() >= 0)
{
logLikelihood.TransferFromDeviceToDevice(
logLikelihood.GetDeviceId(), CPUDEVICE, true, false, false);
}
size_t currentMBSize = pMBLayout->GetNumTimeSteps();
for (size_t i = 0; i < uttInfo.size(); ++i)
{
assert(uttInfo[i].size() == uttInfoInMinibatch[i].size());
for (size_t j = 0; j < uttInfo[i].size(); ++j)
{
wstring uttID = uttInfo[i][j].first;
if (m_uttPool.find(uttID) == m_uttPool.end())
{
UtteranceDerivativeUnit tmpUttUnit;
tmpUttUnit.hasDerivative = false;
tmpUttUnit.uttLength = uttInfo[i][j].second;
tmpUttUnit.progress = 0;
tmpUttUnit.streamID = i;
tmpUttUnit.logLikelihood.Resize(logLikelihood.GetNumRows(),
tmpUttUnit.uttLength);
m_uttPool[uttID] = std::move(tmpUttUnit);
}
// Sets the likelihood and computes derivatives.
assert(m_uttPool.find(uttID) != m_uttPool.end());
if (m_uttPool[uttID].hasDerivative == false)
{
assert(uttID == uttInfoInMinibatch[i][j].first);
size_t startFrame = uttInfoInMinibatch[i][j].second.first;
size_t numFrames = uttInfoInMinibatch[i][j].second.second;
assert(m_uttPool[uttID].progress + numFrames <= m_uttPool[uttID].uttLength);
// Sets the likelihood.
for (size_t k = 0; k < numFrames; ++k)
{
m_uttPool[uttID].logLikelihood.SetColumn(