pub fn train<T, I, S>(&mut self, trainer: &mut T, sequences: I) -> Result<&mut Self>
    where
        T: Trainer<Model = M> + Sync,
        I: Iterator<Item = S> + Send,
        S: AsRef<str> + Send,
    {
        let (lower, upper) = sequences.size_hint();
        let len = upper.unwrap_or(lower) as u64;
        let progress = if trainer.should_show_progress() {
            let progress = ProgressBar::new(len);
            progress.set_style(
                ProgressStyle::default_bar()
                    .template("[{elapsed_precise}] {msg:<40!} {wide_bar} {pos:<9!}/{len:>9!}"),
            );
            progress.set_message("Pre-processing sequences");
            if len > 0 {
                progress.set_draw_delta(len / 100); // Redraw only every 2%
            } else {
                // Trying to have a good default to avoid progress tracking being the bottleneck
                progress.set_draw_delta(1000);
            }
            Some(progress)
        } else {
            None
        };

        trainer.feed(
            sequences.map(|s| {
                if let Some(progress) = &progress {
                    progress.inc(1)
                }
                s
            }),
            |seq| {
                let normalized = self.do_normalize(seq.as_ref())?;
                let pre_tokenized = self.do_pre_tokenize(normalized)?;
                Ok(pre_tokenized
                    .get_splits(OffsetReferential::Original, OffsetType::Byte)
                    .into_iter()
                    .map(|(s, _, _)| s.to_owned())
                    .collect())
            },
        )?;
        if let Some(pbar) = progress {
            pbar.finish();
        }

        let special_tokens = trainer.train(&mut self.model)?;
        self.add_special_tokens(&special_tokens);

        Ok(self)
    }
/// Train our Model, using the given Trainer and iterator
Train our Model, using the given Trainer and iterator
Train our Model using the given Trainer and iterator
pub fn train<T, I, S>(&mut self, trainer: &mut T, sequences: I) -> Result<&mut Self>
    where
        T: Trainer<Model = M> + Sync,
        I: Iterator<Item = S> + Send,
        S: AsRef<str> + Send,
    {
        let (lower, upper) = sequences.size_hint();
        let len = upper.unwrap_or(lower) as u64;
        let progress = if trainer.should_show_progress() {
            let progress = ProgressBar::new(len);
            progress.set_style(
                ProgressStyle::default_bar()
                    .template("[{elapsed_precise}] {msg:<40!} {wide_bar} {pos:<9!}/{len:>9!}"),
            );
            progress.set_message("Pre-processing sequences");
            if len > 0 {
                progress.set_draw_delta(len / 100); // Redraw only every 2%
            } else {
                // Trying to have a good default to avoid progress tracking being the bottleneck
                progress.set_draw_delta(1000);
            }
            Some(progress)
        } else {
            None
        };
        trainer.feed(
            sequences.map(|s| {
                if let Some(progress) = &progress {
                    progress.inc(1)
                }
                s
            }),
            |seq| {
                let normalized = self.do_normalize(seq.as_ref())?;
                let pre_tokenized = self.do_pre_tokenize(normalized)?;
                Ok(pre_tokenized
                    .get_splits(OffsetReferential::Original, OffsetType::Byte)
                    .into_iter()
                    .map(|(s, _, _)| s.to_owned())
                    .collect())
            },
        )?;
        if let Some(pbar) = progress {
            pbar.finish();
        }
        let special_tokens = trainer.train(&mut self.model)?;
        self.add_special_tokens(&special_tokens);
        Ok(self)
    }
pub fn train < T , I , S > ( & mut self , trainer : & mut T , sequences : I ) -> Result < & mut Self > where T : Trainer < Model = M > + Sync , I : Iterator < Item = S > + Send , S : AsRef < str > + Send , { let ( lower , upper ) = sequences . size_hint ( ) ; let len = upper . unwrap_or ( lower ) as u64 ; let progress = if trainer . should_show_progress ( ) { let progress = ProgressBar :: new ( len ) ; progress . set_style ( ProgressStyle :: default_bar ( ) . template ( " " ) , ) ; progress . set_message ( " " ) ; if len > 0 { progress . set_draw_delta ( len / 100 ) ; // Redraw only every 2% } else { // Trying to have a good default to avoid progress tracking being the bottleneck progress . set_draw_delta ( 1000 ) ; } Some ( progress ) } else { None } ; trainer . feed ( sequences . map ( | s | { if let Some ( progress ) = & progress { progress . inc ( 1 ) } s } ) , | seq | { let normalized = self . do_normalize ( seq . as_ref ( ) ) ? ; let pre_tokenized = self . do_pre_tokenize ( normalized ) ? ; Ok ( pre_tokenized . get_splits ( OffsetReferential :: Original , OffsetType :: Byte ) . into_iter ( ) . map ( | ( s , _ , _ ) | s . to_owned ( ) ) . collect ( ) ) } , ) ? ; if let Some ( pbar ) = progress { pbar . finish ( ) ; } let special_tokens = trainer . train ( & mut self . model ) ? ; self . add_special_tokens ( & special_tokens ) ; Ok ( self ) }
Train our Model, using the given Trainer and iterator
Train our Model using the given Trainer and iterator
&mut self
trainer
&mut T
sequences
I