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namespace InferenceEngine::NetPass

Overview

namespace NetPass {

// global functions

bool CombineRNNSeq(CNNNetwork& net);
bool CombineRNNSeq(TensorIterator::Body& net);
std::vector<CNNLayerPtr> TIBodySortTopologically(const TensorIterator::Body& body);
bool HasInternalSubnet(const CNNLayerPtr& layer);
details::CNNSubnet GetInternalSubnet(const CNNLayerPtr& layer);
bool UnrollTI(CNNNetwork& net);
bool UnrollRNN_if(CNNNetwork& net, std::function<bool(const RNNCellBase&)> pred);

TensorIterator::Body CopyTIBody(
    const TensorIterator::Body& body,
    std::string suffix = std::string()
    );

bool UnrollRNN_if(
    TensorIterator::Body& net,
    std::function<bool(const RNNCellBase&)> pred
    );

void ConvertPrecision(CNNNetwork& net, Precision from, Precision to);
void ConvertIOPrecision(CNNNetwork& net, Precision from, Precision to);

} // namespace NetPass

Detailed Documentation

Global Functions

bool CombineRNNSeq(CNNNetwork& net)

Try to detect LSTM Sequence pattern inside TI and convert it

Parameters:

net	network to modify

Returns:

true if all Tensor iterator was converted

std::vector<CNNLayerPtr> TIBodySortTopologically(const TensorIterator::Body& body)

Returns a vector of the topologically sorted layers from the passed TI layer body.

Parameters:

body

TI body

Returns:

vector of layer objects

bool HasInternalSubnet(const CNNLayerPtr& layer)

Check if provided layer contains internal attribute like subnet/subgraph

Parameters:

layer

to check

Returns:

true if layer has subnet

details::CNNSubnet GetInternalSubnet(const CNNLayerPtr& layer)

Extract internal subnet from layer

All internal layers are returned by reference. Any modification further subnet modification will has affect on original layer state.

Parameters:

layer

to proceed

Returns:

internal subnet

bool UnrollTI(CNNNetwork& net)

Unroll all present Tensor Iterators

Parameters:

net	network to modify

Returns:

true if all Tensor iterator was unrolled successfully

bool UnrollRNN_if(CNNNetwork& net, std::function<bool(const RNNCellBase&)> pred)

Unroll all RNN specific layers by predicate

Will be applied to all RNNSeq and RNNCell layers

Parameters:

net	network to modify
pred	predicate to mark layer to unroll

Returns:

true if all RNN layers was unrolled successfully

TensorIterator::Body CopyTIBody(
    const TensorIterator::Body& body,
    std::string suffix = std::string()
    )

Construct a copy of provided subnet. Will change names by adding suffix if it was provided.

Parameters:

subnet	to copy from
suffix	is optional attribute. Will be added into name of each layer/data object if provided

Returns:

subnet copy. Each layer/data object is newly created. Const blob objects is inherited from original subnet.

void ConvertPrecision(CNNNetwork& net, Precision from, Precision to)

Precision conversion pass

Will perform conversion of all presented tensors with specified precision including const blobs and intermediate tensors. It doesn’t check layer semantic. It may break correctness of topology.

It also remove redundant convert layers if they will appear.

Parameters:

net	is network to apply conversion
from	precision of tensors required conversion
to	resulting precision of tensors