plotly

Documentation

Overview

Package plotly uses GoNB plotly support (`github.com/janpfeifer/gonb/gonbui/plotly`) to plot both on dynamic plots while training or to quickly plot the results of a previously saved plot results in a checkpoints directory.

In either case it allows adding baseline plots of previous checkpoints.

The advantage of `plotly` over `margaid` plots is that it uses Javascript to make the plot interactive (it displays information on mouse hover).

The disadvantage is that saving doesn't work, because of the javascript nature.

Index

• type PlotConfig
  • func New() *PlotConfig
  • func (pc *PlotConfig) AddPoint(pt plots.Point)
  • func (pc *PlotConfig) Dynamic(datasets ...train.Dataset) *PlotConfig
  • func (pc *PlotConfig) DynamicPlot(final bool)
  • func (pc *PlotConfig) DynamicSampleDone(incomplete bool)
  • func (pc *PlotConfig) LoadCheckpointData(dataDirOrFile string, filters ...PointFilter) error
  • func (pc *PlotConfig) Plot() error
  • func (pc *PlotConfig) ScheduleExponential(loop *train.Loop, startStep int, stepFactor float64) *PlotConfig
  • func (pc *PlotConfig) ScheduleNTimes(loop *train.Loop, numPoints int) *PlotConfig
  • func (pc *PlotConfig) WithCheckpoint(checkpointDir string) *PlotConfig
• type PointFilter

Types

type PlotConfig

type PlotConfig struct {

	// EvalDatasets registered to be used during evaluation when dynamically capturing points during training.
	EvalDatasets []train.Dataset
	// contains filtered or unexported fields
}

PlotConfig hold the configuration object that will generate the plot. Create it with New.

func New

func New() *PlotConfig

New creates a new PlotConfig, that can be used to generate plots.

func (*PlotConfig) AddPoint

func (pc *PlotConfig) AddPoint(pt plots.Point)

AddPoint add one point to the plots.

Usually not called directly, instead use [LoadCheckpointData] or [Dynamic], which will attach to a training loop and call this automatically.

func (*PlotConfig) Dynamic

func (pc *PlotConfig) Dynamic(datasets ...train.Dataset) *PlotConfig

Dynamic sets plot to be dynamically updated and new data comes in. It's a no-op if not running in a GoNB notebook.

`datasets` is a list of datasets to be evaluated when collecting metrics for plotting.

It should be followed by a call to [ScheduleExponential] or [SechedulePeriodic] (or both) to schedule capturing points to plot, and [WithCheckpoint] to save the captured points.

It returns itself to allow cascading configuration method calls.

func (*PlotConfig) DynamicPlot

func (pc *PlotConfig) DynamicPlot(final bool)

DynamicPlot is called everytime a new metrics comes in, if configured for dynamic updates. Usually, not called directly by the user. Simply use [Dynamic] and schedule updates and this function will be called automatically.

If `final` is true, it clears the transient area, and it plots instead in the definitive version.

func (*PlotConfig) DynamicSampleDone

func (pc *PlotConfig) DynamicSampleDone(incomplete bool)

DynamicSampleDone is called after all the data points recorded for this sample (evaluation at a time step). The value `incomplete` is set to true if any of the evaluations are NaN or infinite.

If in a notebook, this would trigger a redraw of the plot.

It implements [plot.Plotter]

func (*PlotConfig) LoadCheckpointData

func (pc *PlotConfig) LoadCheckpointData(dataDirOrFile string, filters ...PointFilter) error

LoadCheckpointData loads plotting data from a checkpoint path. Notice this only works if the model was trained with plotting, with the metrics saved into the file `training_plot_points.json` (plots.TrainingPlotFileName). Notice that if `dataDirOrFile` is a file it reads from that instead.

The `filters` are an optional list of filters to apply (in order) to each of the points read: it allows points to be modified arbitrarily -- in particular useful to change names (like adding a prefix) of metrics or metrics types.

Each filter can also eliminate points by returning false -- only points for which filters returned true are included.

func (*PlotConfig) Plot

func (pc *PlotConfig) Plot() error

Plot all figures with current data. If not in a notebook, this is a no-op.

func (*PlotConfig) ScheduleExponential

func (pc *PlotConfig) ScheduleExponential(loop *train.Loop, startStep int, stepFactor float64) *PlotConfig

ScheduleExponential collection of plot points, starting at `startStep` and with an increasing step factor of `stepFactor`. Typical values where could be 100 and 1.1.

It returns itself to allow cascading configuration method calls.

func (*PlotConfig) ScheduleNTimes

func (pc *PlotConfig) ScheduleNTimes(loop *train.Loop, numPoints int) *PlotConfig

ScheduleNTimes of collection of plot points.

It returns itself to allow cascading configuration method calls.

func (*PlotConfig) WithCheckpoint

func (pc *PlotConfig) WithCheckpoint(checkpointDir string) *PlotConfig

WithCheckpoint uses the `checkpointDir` both to load data points and to save any new data points. Usually, used with PlotConfig.Dynamic.

New data-points are saved asynchronously -- not to slow down training, with the downside of potentially having I/O issues reported asynchronously.

It returns itself to allow cascading configuration method calls.

type PointFilter

type PointFilter func(p *plots.Point) bool

PointFilter can change any plots.Point arbitrarily. If it returns false means the point should be dropped.