Struct Args 

pub struct Args {

    pub input: String,
    pub output: String,
    pub backend: String,
    pub directed: bool,
    pub embedding_dim: usize,
    pub split: f32,
    pub walks_per_node: usize,
    pub walk_length: usize,
    pub window_size: usize,
    pub batch_size: usize,
    pub num_workers: usize,
    pub num_epochs: usize,
    pub num_negatives: usize,
    pub seed: usize,
    pub learning_rate: f64,
    pub p: f32,
    pub q: f32,
    pub sample: f32,
}

CLI arguments

Fields

• input - The input CSV. Needs to be provided.
• output - Where to store the outputs. Defaults to "/tmp/node2vec".
• directed - Shall the graph be treated as a directed graph. Defaults to false.
• embedding_dim - Size of the embedding to create. Defaults to 16.
• split - How much of the data should be in the trainings data vs. validation data. Defaults to 0.9.
• walks_per_node - Number of random walks to do per node. Defaults to 20.
• walk_length - Length of the random walks. Defaults to 20.
• window_size - Window size parameter for the skipgram model. Defaults to 2.
• batch_size - Batch size during training. Defaults to 256.
• num_workers - Number of workers to use during the generation of the batches. Defaults to 4.
• num_epochs - Number of epochs to train the model for. Defaults to 5.
• num_negatives - Number of negative examples to sample. Defaults to 5.
• seed - Seed for reproducibility. Defaults to 42.
• learning_rate - Learning rate for the Adam optimiser. Defaults to 1-e3.
• p - p parameter for the node2vec random walks and controls the probability to return to origin node. Defaults to 1.0.
• q - q parameter for node2vec random walks and controls the probability to venture on a different node from the origin node. Defaults to 1.0.

Fields

input: String

output: String

backend: String

directed: bool

embedding_dim: usize

split: f32

walks_per_node: usize

walk_length: usize

window_size: usize

batch_size: usize

num_workers: usize

num_epochs: usize

num_negatives: usize

seed: usize

learning_rate: f64

p: f32

q: f32

sample: f32

Trait Implementations

impl Args for Args

fn group_id() -> Option<Id>

Report the ArgGroup::id for this set of arguments

fn augment_args<'b>(__clap_app: Command) -> Command

Append to Command so it can instantiate Self via FromArgMatches::from_arg_matches_mut

fn augment_args_for_update<'b>(__clap_app: Command) -> Command

Append to Command so it can instantiate self via FromArgMatches::update_from_arg_matches_mut

impl CommandFactory for Args

fn command<'b>() -> Command

Build a Command that can instantiate Self.

fn command_for_update<'b>() -> Command

Build a Command that can update self.

impl FromArgMatches for Args

fn from_arg_matches(__clap_arg_matches: &ArgMatches) -> Result<Self, Error>

Instantiate Self from ArgMatches, parsing the arguments as needed.

fn from_arg_matches_mut( __clap_arg_matches: &mut ArgMatches, ) -> Result<Self, Error>

Instantiate Self from ArgMatches, parsing the arguments as needed.

fn update_from_arg_matches( &mut self, __clap_arg_matches: &ArgMatches, ) -> Result<(), Error>

Assign values from ArgMatches to self.

fn update_from_arg_matches_mut( &mut self, __clap_arg_matches: &mut ArgMatches, ) -> Result<(), Error>

Assign values from ArgMatches to self.

impl Parser for Args

fn parse() -> Self

Parse from std::env::args_os(), exit on error.

fn try_parse() -> Result<Self, Error>

Parse from std::env::args_os(), return Err on error.

fn parse_from<I, T>(itr: I) -> Self

where I: IntoIterator<Item = T>, T: Into<OsString> + Clone,

Parse from iterator, exit on error.

fn try_parse_from<I, T>(itr: I) -> Result<Self, Error>

where I: IntoIterator<Item = T>, T: Into<OsString> + Clone,

Parse from iterator, return Err on error.

fn update_from<I, T>(&mut self, itr: I)

where I: IntoIterator<Item = T>, T: Into<OsString> + Clone,

Update from iterator, exit on error.

fn try_update_from<I, T>(&mut self, itr: I) -> Result<(), Error>

where I: IntoIterator<Item = T>, T: Into<OsString> + Clone,

Update from iterator, return Err on error.