mnist

Documentation

Overview

package mnist handles the mnist data set

package mnist handles the mnist data set

Index

• Constants
• func NewMnistDataset(dataloc string, epochs int) dataset.Dataset
• type Label
• type MnistDataset
  • func (fd *MnistDataset) Epochs() int
  • func (fd *MnistDataset) TestRatio() float64
  • func (fd *MnistDataset) XY() (tensor.Tensor, tensor.Tensor, error)
• type RawImage

Constants

const (

	// Width of the input tensor / picture
	Width = 28
	// Height of the input tensor / picture
	Height = 28
)

Functions

func NewMnistDataset

func NewMnistDataset(dataloc string, epochs int) dataset.Dataset

NewMnistDataset wil create a new MnistDataset instance.

Types

type Label

type Label uint8

Label is a digit label in 0 to 9

type MnistDataset

type MnistDataset struct {
	// contains filtered or unexported fields
}

MnistDataset is the object that describes the mnist dataset.

func (*MnistDataset) Epochs

func (fd *MnistDataset) Epochs() int

Epochs returns the number of epochs that should run during training.

func (*MnistDataset) TestRatio

func (fd *MnistDataset) TestRatio() float64

TestRatio returns how much can of the dataset can be used for validating the network.

func (*MnistDataset) XY

func (fd *MnistDataset) XY() (tensor.Tensor, tensor.Tensor, error)

XY returns the data to be trained.

type RawImage

type RawImage []byte

Image holds the pixel intensities of an image. 255 is foreground (black), 0 is background (white).