nmtSample Namespace Reference

Classes
class	Alignment
	represents the core of attention mechanism More...
class	Attention
	calculates attention vector from context and decoder output vectors More...
class	BeamSearchPolicy
	processes the results of one iteration of the generator with beam search and produces input for the next iteration More...
class	BenchmarkWriter
	all it does is to measure the performance of sequence generation More...
class	BLEUScoreWriter
	all it does is to evaluate BLEU score More...
class	Component
	a functional part of the sample More...
class	ComponentWeights
	weights storage More...
class	Context
	calculates context vector from raw alignment scores and memory states More...
class	DataReader
	reader of sequences of data More...
class	DataWriter
	writer of sequences of data More...
class	DebugUtil
	container for static debug utility functions More...
class	Decoder
	encodes single input into output states More...
class	DeviceBuffer
class	Embedder
	projects 1-hot vectors (represented as a vector with indices) into dense embedding space More...
class	Encoder
	encodes input sentences into output states More...
class	Likelihood
	calculates likelihood and TopK indices for the raw input logits More...
class	LikelihoodCombinationOperator
class	LimitedSamplesDataReader
	wraps another data reader and limits the number of samples to read More...
class	LSTMDecoder
	encodes single input into output states with LSTM More...
class	LSTMEncoder
	encodes input sentences into output states using LSTM More...
class	MultiplicativeAlignment
	alignment scores from Luong attention mechanism More...
class	PinnedHostBuffer
	wrapper for the pinned host memory region More...
class	Projection
	calculates raw logits More...
class	SequenceProperties
	provides encoder/decoder relevant properties of sequences More...
class	SLPAttention
	Linear attention calculation. More...
class	SLPEmbedder
	selects the embedding vector from the weight matrix using index provided in the input More...
class	SLPProjection
	Linear logits calculation. More...
class	SoftmaxLikelihood
	calculates softmax likelihood and TopK indices for the raw input logits More...
class	TextReader
	reads sequences of data from input stream More...
class	TextWriter
class	Vocabulary
	String<->Id bijection storage. More...

Typedefs
typedef std::vector< std::string >	Segment_t
typedef std::map< Segment_t, int >	Count_t

Functions
int	read (std::vector< Segment_t > &samples, std::shared_ptr< std::istream > input, int samplesToRead=1)
Count_t	ngramCounts (const Segment_t &segment, int maxOrder=4)
Count_t	ngramCountIntersection (const Count_t &cnt0, const Count_t &cnt1)
void	accumulateBLEU (const std::vector< Segment_t > &referenceSamples, const std::vector< Segment_t > &outputSamples, int maxOrder, size_t &referenceLength, size_t &translationLength, std::vector< size_t > &matchesByOrder, std::vector< size_t > &possibleMatchesByOrder)
std::istream &	operator>> (std::istream &input, Vocabulary &value)
std::istream &	operator>> (std::istream &input, ComponentWeights &value)
int	inferTypeToBytes (nvinfer1::DataType t)
int	getVolume (nvinfer1::Dims dims)
std::vector< float >	resizeWeights (int rows, int cols, int rowsNew, int colsNew, const float *memory)

Typedef Documentation

Segment_t

typedef std::vector<std::string> nmtSample::Segment_t

Count_t

typedef std::map<Segment_t, int> nmtSample::Count_t

Function Documentation

read()

int nmtSample::read	(	std::vector< Segment_t > &	samples,
		std::shared_ptr< std::istream >	input,
		int	samplesToRead = 1
	)

Here is the caller graph for this function:

ngramCounts()

Count_t nmtSample::ngramCounts	(	const Segment_t &	segment,
		int	maxOrder = 4
	)

Here is the caller graph for this function:

ngramCountIntersection()

Count_t nmtSample::ngramCountIntersection	(	const Count_t &	cnt0,
		const Count_t &	cnt1
	)

Here is the caller graph for this function:

accumulateBLEU()

void nmtSample::accumulateBLEU	(	const std::vector< Segment_t > &	referenceSamples,
		const std::vector< Segment_t > &	outputSamples,
		int	maxOrder,
		size_t &	referenceLength,
		size_t &	translationLength,
		std::vector< size_t > &	matchesByOrder,
		std::vector< size_t > &	possibleMatchesByOrder
	)

Here is the call graph for this function:

Here is the caller graph for this function:

operator>>() [1/2]

std::istream& nmtSample::operator>>	(	std::istream &	input,
		Vocabulary &	value
	)

Here is the call graph for this function:

operator>>() [2/2]

std::istream& nmtSample::operator>>	(	std::istream &	input,
		ComponentWeights &	value
	)

inferTypeToBytes()

int nmtSample::inferTypeToBytes

(

nvinfer1::DataType

t

)

Here is the caller graph for this function:

getVolume()

int nmtSample::getVolume

(

nvinfer1::Dims

dims

)

resizeWeights()

std::vector< float > nmtSample::resizeWeights	(	int	rows,
		int	cols,
		int	rowsNew,
		int	colsNew,
		const float *	memory
	)

Here is the caller graph for this function: