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Versions in this module

v0

v0.26.28

Mar 22, 2022

Changes in this version

type Batch

+ ClassWeights *tf.Tensor

type Dataset

+ NumCategoricalClasses func() int

+ SaveProcessors func(saveDir string) error

+ type ImgFolderDataset struct

+ ClassCounts map[int]int

+ ClassWeights map[int]float32

+ Count int

+ func NewImgFolderDataset(logger *cblog.Logger, errorHandler *cberrors.ErrorsContainer, ...) (*ImgFolderDataset, error)

+ func (d *ImgFolderDataset) Generate(batchSize int) ([]*tf.Tensor, *tf.Tensor, *tf.Tensor, error)

+ func (d *ImgFolderDataset) GeneratorChan(batchSize int, preFetch int) chan Batch

+ func (d *ImgFolderDataset) GetColumnNames() []string

+ func (d *ImgFolderDataset) Len() int

+ func (d *ImgFolderDataset) NumCategoricalClasses() int

+ func (d *ImgFolderDataset) Reset() error

+ func (d *ImgFolderDataset) SaveProcessors(saveDir string) error

+ func (d *ImgFolderDataset) SetMode(mode GeneratorMode) Dataset

+ func (d *ImgFolderDataset) Shuffle(seed int64)

+ func (d *ImgFolderDataset) Unshuffle() error

+ type ImgFolderDatasetConfig struct

+ CacheDir string

+ ClassWeights map[int]float32

+ ConcurrentFileLimit int32

+ IgnoreParseErrors bool

+ ParentDir string

+ TestPercent float32

+ TrainPercent float32

+ ValPercent float32

+ type Inference struct

+ func NewInference(logger *cblog.Logger, errorHandler *cberrors.ErrorsContainer, ...) (*Inference, error)

+ func (d *Inference) GenerateInputs(rawInputValues ...interface{}) ([]*tf.Tensor, error)

+ func (d *Inference) GetColumnNames() []string

type SingleFileDataset

+ ClassWeights map[int]float32

+ func (d *SingleFileDataset) NumCategoricalClasses() int

+ func (d *SingleFileDataset) SaveProcessors(saveDir string) error

+ type SingleFileDatasetConfig struct

+ CacheDir string

+ ClassWeights map[int]float32

+ ConcurrentFileLimit int32

+ FilePath string

+ IgnoreParseErrors bool

+ MaxRowsForProcessorFit int

+ RowFilter func(line []string) bool

+ SkipHeaders bool

+ TestPercent float32

+ TrainPercent float32

+ ValPercent float32

+ type ValuesDataset struct

+ ClassCounts map[int]int

+ ClassWeights map[int]float32

+ Count int

+ func NewValuesDataset(logger *cblog.Logger, errorHandler *cberrors.ErrorsContainer, ...) (*ValuesDataset, error)

+ func (d *ValuesDataset) Generate(batchSize int) ([]*tf.Tensor, *tf.Tensor, *tf.Tensor, error)

+ func (d *ValuesDataset) GeneratorChan(batchSize int, preFetch int) chan Batch

+ func (d *ValuesDataset) GetColumnNames() []string

+ func (d *ValuesDataset) Len() int

+ func (d *ValuesDataset) NumCategoricalClasses() int

+ func (d *ValuesDataset) Reset() error

+ func (d *ValuesDataset) SaveProcessors(saveDir string) error

+ func (d *ValuesDataset) SetMode(mode GeneratorMode) Dataset

+ func (d *ValuesDataset) SetValues(yValues []interface{}, xValues ...[]interface{}) error

+ func (d *ValuesDataset) Shuffle(seed int64)

+ func (d *ValuesDataset) Unshuffle() error

+ type ValuesDatasetConfig struct

+ CacheDir string

+ TestPercent float32

+ TrainPercent float32

+ ValPercent float32

v0.2.6

Dec 6, 2021

Changes in this version

+ type Batch struct

+ NegWeight *tf.Tensor

+ PosWeight *tf.Tensor

+ X []*tf.Tensor

+ Y *tf.Tensor

+ type Dataset interface

+ Generate func(batchSize int) ([]*tf.Tensor, *tf.Tensor, error)

+ GeneratorChan func(batchSize int, preFetch int) chan Batch

+ GetColumnNames func() []string

+ Len func() int

+ Reset func() error

+ SetMode func(mode GeneratorMode) Dataset

+ Shuffle func(seed int64)

+ Unshuffle func() error

+ type GeneratorMode string

+ var ErrGeneratorEnd = errors.New("end of data")

+ var GeneratorModeTest GeneratorMode = "test"

+ var GeneratorModeTrain GeneratorMode = "train"

+ var GeneratorModeVal GeneratorMode = "val"

+ type SingleFileDataset struct

+ ClassCounts map[int]int

+ Count int

+ func NewSingleFileDataset(logger *cblog.Logger, errorHandler *cberrors.ErrorsContainer, filePath string, ...) (*SingleFileDataset, error)

+ func (d *SingleFileDataset) Generate(batchSize int) ([]*tf.Tensor, *tf.Tensor, error)

+ func (d *SingleFileDataset) GeneratorChan(batchSize int, preFetch int) chan Batch

+ func (d *SingleFileDataset) GetColumnNames() []string

+ func (d *SingleFileDataset) Len() int

+ func (d *SingleFileDataset) Reset() error

+ func (d *SingleFileDataset) SetMode(mode GeneratorMode) Dataset

+ func (d *SingleFileDataset) Shuffle(seed int64)

+ func (d *SingleFileDataset) Unshuffle() error