Metavoice position fix (#1791)

* Add the metavoice transformer.

* Sketch the speaker-encoder module.

* Adding to the metavoice model.

* Start adding the metavoice example.

* Get some logits out.

* Load the second stage model.

* Get the second step to run.

* Tweak the example.

* Add encodec tilting.

* Glue the different bits together.

* Fix a shape issue.

* Use a constant.

* BPE tokenization.

* Fix the position index in metavoice.

candle-examples/examples/metavoice/main.rs

@@ -44,6 +44,10 @@ struct Args {
     #[arg(long, default_value_t = 299792458)]
     seed: u64,
 
+    /// The maximum number of tokens to generate for the first stage.
+    #[arg(long, default_value_t = 2000)]
+    max_tokens: u64,
+
     /// The output file using the wav format.
     #[arg(long, default_value = "out.wav")]
     out_file: String,
@@ -148,19 +152,18 @@ fn main() -> Result<()> {
     let mut logits_processor = LogitsProcessor::new(args.seed, Some(args.temperature), None);
 
     // First stage generation.
-    for index in 0.. {
+    for index in 0..args.max_tokens {
         let context_size = if index > 0 { 1 } else { tokens.len() };
         let start_pos = tokens.len().saturating_sub(context_size);
         let ctxt = &tokens[start_pos..];
         let input = Tensor::new(ctxt, &device)?;
         let input = Tensor::stack(&[&input, &input], 0)?;
-        let logits = first_stage_model.forward(&input, &spk_emb, index)?;
+        let logits = first_stage_model.forward(&input, &spk_emb, tokens.len() - context_size)?;
         let logits0 = logits.i((0, 0))?;
         let logits1 = logits.i((1, 0))?;
         let logits = ((logits0 * args.guidance_scale)? + logits1 * (1. - args.guidance_scale))?;
         let logits = logits.to_dtype(DType::F32)?;
         let next_token = logits_processor.sample(&logits)?;
-        println!("{} {next_token}", tokens.len());
         tokens.push(next_token);
         if next_token == 2048 {
             break;
@@ -183,9 +186,9 @@ fn main() -> Result<()> {
     let in_x2 = Tensor::new(hierarchies_in2, &device)?;
     let in_x = Tensor::stack(&[in_x1, in_x2], 0)?.unsqueeze(0)?;
     let logits = second_stage_model.forward(&in_x)?;
+    println!("sampling from logits...");
     let mut codes = vec![];
-    for (idx, logits) in logits.iter().enumerate() {
-        println!("{idx} {logits}");
+    for logits in logits.iter() {
         let logits = logits.squeeze(0)?;
         let (seq_len, _) = logits.dims2()?;
         let mut codes_ = Vec::with_capacity(seq_len);