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[habana] Misc fixes for vision nets #2838

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May 2, 2019
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[habana] Misc fixes for vision nets #2838

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61 changes: 51 additions & 10 deletions lib/Backends/Habana/Habana.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -548,10 +548,10 @@ makeSynPoolParams(llvm::ArrayRef<unsigned_t> kernel,
params->sW = stride[0];
params->sH = stride[1];
// Padding
params->pWbegin = pad[0];
params->pWend = pad[0];
params->pHbegin = pad[1];
params->pHend = pad[1];
params->pHbegin = pad[0];
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Lol, whoops.

params->pWbegin = pad[1];
params->pHend = pad[2];
params->pWend = pad[3];
// Dilation
params->dilW = 1;
params->dilH = 1;
Expand Down Expand Up @@ -591,6 +591,16 @@ makeSynSliceAxisParams(unsigned axis, unsigned axes, unsigned outputAxisSize,
return params;
}

static std::unique_ptr<ns_LrnKernel::Params>
makeLrnParams(float alpha, float beta, float knorm, int halfWindowSize) {
auto params = llvm::make_unique<ns_LrnKernel::Params>();
params->alpha = alpha;
params->beta = beta;
params->knorm = knorm;
params->nsize = 2 * halfWindowSize + 1;
return params;
}

static std::unique_ptr<ns_ConstantKernel::Params>
makeConstantParams(float value) {
auto params = llvm::make_unique<ns_ConstantKernel::Params>();
Expand Down Expand Up @@ -733,6 +743,8 @@ HabanaBackend::compile(Function *F, const BackendOptions &opts) const {
std::vector<std::unique_ptr<ns_TileKernel::Params>> tileParams;
std::vector<std::unique_ptr<unsigned>> concatParams;
std::vector<std::unique_ptr<ns_TakeKernel::Params>> takeParams;
std::vector<std::unique_ptr<ns_LrnKernel::Params>> lrnParams;
std::vector<std::unique_ptr<synGEMMParams>> gemmParams;

// Keep references to tensor pointer arrays passed into multi-input nodes
// until the compilation is done.
Expand Down Expand Up @@ -965,12 +977,16 @@ HabanaBackend::compile(Function *F, const BackendOptions &opts) const {
if (MI->getLHS().getType()->isQuantizedType()) {
// Let GEMM run on MME via FullyConnected node.
// MME only runs on quantized types, e.g., int8 or int16.
auto params = llvm::make_unique<synFCParams>();
params->activation.reluEnable = false;
chk(synFullyConnected(tensors[MI->getLHS()].get(),
tensors[MI->getRHS()].get(), nullptr,
tensors[MI].get(), *params, ""));
fcParams.emplace_back(std::move(params));
// The default params are OK - don't transpose A and B
auto params = llvm::make_unique<synGEMMParams>();
std::vector<synTensor> inputs;
inputs.push_back(tensors[MI->getLHS()].get());
inputs.push_back(tensors[MI->getRHS()].get());
chk(synCreateGenericNode(inputs.data(), &tensors[MI].get(),
inputs.size(), 1, nullptr, "gemm",
MI->getName().data(), nullptr, nullptr));
gemmParams.emplace_back(std::move(params));

} else {
std::vector<synTensor> inputs;
inputs.push_back(tensors[MI->getLHS()].get());
Expand Down Expand Up @@ -1015,6 +1031,18 @@ HabanaBackend::compile(Function *F, const BackendOptions &opts) const {
convParams.emplace_back(std::move(params));
break;
}
case Kinded::Kind::LocalResponseNormalizationNodeKind: {
auto *NI = llvm::cast<LocalResponseNormalizationNode>(&I);
std::unique_ptr<ns_LrnKernel::Params> params = makeLrnParams(
NI->getAlpha(), NI->getBeta(), NI->getK(), NI->getHalfWindowSize());

chk(synCreateGenericNode(&tensors[NI->getInput()].get(),
&tensors[NI].get(), 1, 1, (void *)params.get(),
"lrn_f32", NI->getName().str().c_str(), nullptr,
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Is the datatype intentionally hardcoded? Does this operator not exist for other datatypes? It makes sense that it wouldn't, but I just want to confirm.

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Good eye - LRN does indeed only exist for f32. We could assert that here, although it'll already be caught by isOpSupported.

nullptr));
lrnParams.emplace_back(std::move(params));
break;
}
case Kinded::Kind::TransposeNodeKind: {
auto *TI = llvm::cast<TransposeNode>(&I);
std::unique_ptr<synTransposeParams> params =
Expand Down Expand Up @@ -1126,6 +1154,14 @@ HabanaBackend::compile(Function *F, const BackendOptions &opts) const {
concatParams.emplace_back(std::move(params));
break;
}
case Kinded::Kind::RescaleQuantizedNodeKind: {
auto *RI = llvm::cast<RescaleQuantizedNode>(&I);
chk(synCreateGenericNode(
&tensors[RI->getInput()].get(), &tensors[RI].get(), 1, 1, nullptr,
getKernelName("requant", RI->getResult().getElementType()).c_str(),
RI->getName().data(), nullptr, nullptr));
break;
}
case Kinded::Kind::SaveNodeKind: {
auto *CI = llvm::cast<SaveNode>(&I);
if (tensors.count(CI)) {
Expand Down Expand Up @@ -1237,7 +1273,11 @@ bool HabanaBackend::isOpSupported(const NodeInfo &NI) const {
case Kinded::Kind::SplatNodeKind:
case Kinded::Kind::SubNodeKind:
case Kinded::Kind::TileNodeKind:
case Kinded::Kind::ConcatNodeKind:
return true;
case Kinded::Kind::RescaleQuantizedNodeKind:
return NI.allInputsAndOutputsHaveSameElemKind(
{ElemKind::Int8QTy, ElemKind::Int16QTy});
default:
return false;
}
Expand Down Expand Up @@ -1273,6 +1313,7 @@ bool HabanaBackend::isOpSupported(const NodeInfo &NI) const {
case Kinded::Kind::TransposeNodeKind:
case Kinded::Kind::SparseLengthsWeightedSumNodeKind:
case Kinded::Kind::FusedRowwiseQuantizedSparseLengthsWeightedSumNodeKind:
case Kinded::Kind::LocalResponseNormalizationNodeKind:
return true;
default:
return false;
Expand Down