SYMBOL INDEX (33 symbols across 4 files)

FILE: generator.py
  class Segment (line 15) | class Segment:
  function load_llama3_tokenizer (line 22) | def load_llama3_tokenizer():
  class Generator (line 39) | class Generator:
    method __init__ (line 40) | def __init__(
    method _tokenize_text_segment (line 60) | def _tokenize_text_segment(self, text: str, speaker: int) -> Tuple[tor...
    method _tokenize_audio (line 75) | def _tokenize_audio(self, audio: torch.Tensor) -> Tuple[torch.Tensor, ...
    method _tokenize_segment (line 98) | def _tokenize_segment(self, segment: Segment) -> Tuple[torch.Tensor, t...
    method generate (line 109) | def generate(
  function load_csm_1b (line 171) | def load_csm_1b(device: str = "cuda") -> Generator:

FILE: models.py
  function llama3_2_1B (line 10) | def llama3_2_1B() -> torchtune.modules.transformer.TransformerDecoder:
  function llama3_2_100M (line 26) | def llama3_2_100M() -> torchtune.modules.transformer.TransformerDecoder:
  function _prepare_transformer (line 48) | def _prepare_transformer(model):
  function _create_causal_mask (line 55) | def _create_causal_mask(seq_len: int, device: torch.device):
  function _index_causal_mask (line 59) | def _index_causal_mask(mask: torch.Tensor, input_pos: torch.Tensor):
  function _multinomial_sample_one_no_sync (line 72) | def _multinomial_sample_one_no_sync(probs):  # Does multinomial sampling...
  function sample_topk (line 77) | def sample_topk(logits: torch.Tensor, topk: int, temperature: float):
  class ModelArgs (line 91) | class ModelArgs:
  class Model (line 99) | class Model(
    method __init__ (line 106) | def __init__(self, config: ModelArgs):
    method setup_caches (line 120) | def setup_caches(self, max_batch_size: int) -> torch.Tensor:
    method generate_frame (line 132) | def generate_frame(
    method reset_caches (line 186) | def reset_caches(self):
    method _embed_audio (line 190) | def _embed_audio(self, codebook: int, tokens: torch.Tensor) -> torch.T...
    method _embed_tokens (line 193) | def _embed_tokens(self, tokens: torch.Tensor) -> torch.Tensor:

FILE: run_csm.py
  function load_prompt_audio (line 46) | def load_prompt_audio(audio_path: str, target_sample_rate: int) -> torch...
  function prepare_prompt (line 55) | def prepare_prompt(text: str, speaker: int, audio_path: str, sample_rate...
  function main (line 59) | def main():

FILE: watermarking.py
  function cli_check_audio (line 12) | def cli_check_audio() -> None:
  function load_watermarker (line 20) | def load_watermarker(device: str = "cuda") -> silentcipher.server.Model:
  function watermark (line 29) | def watermark(
  function verify (line 44) | def verify(
  function check_audio_from_file (line 62) | def check_audio_from_file(audio_path: str) -> None:
  function load_audio (line 72) | def load_audio(audio_path: str) -> tuple[torch.Tensor, int]: