From e95bcf9d99707379b5f5c09a2988996275f5f467 Mon Sep 17 00:00:00 2001 From: 0xlws Date: Wed, 18 Oct 2023 15:44:40 +0200 Subject: [PATCH] typos: encodec.py --- audiocraft/models/encodec.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/audiocraft/models/encodec.py b/audiocraft/models/encodec.py index 40d13301..4020ee26 100644 --- a/audiocraft/models/encodec.py +++ b/audiocraft/models/encodec.py @@ -25,7 +25,7 @@ class CompressionModel(ABC, nn.Module): - """Base API for all compression model that aim at being used as audio tokenizers + """Base API for all compression models that aim at being used as audio tokenizers with a language model. """ @@ -111,7 +111,7 @@ def get_pretrained( logger.info("Getting pretrained compression model for debug") model = builders.get_debug_compression_model() elif Path(name).exists(): - # We assume here if the paths exist that it is in fact an AC checkpoint + # We assume here if the path exists that it is in fact an AC checkpoint # that was exported using `audiocraft.utils.export` functions. model = loaders.load_compression_model(name, device=device) else: @@ -227,8 +227,8 @@ def encode(self, x: torch.Tensor) -> tp.Tuple[torch.Tensor, tp.Optional[torch.Te Returns: codes, scale (tuple of torch.Tensor, torch.Tensor): Tuple composed of: - codes a float tensor of shape [B, K, T] with K the number of codebooks used and T the timestep. - scale a float tensor containing the scale for audio renormalizealization. + codes: a float tensor of shape [B, K, T] with K the number of codebooks used and T the timestep. + scale: a float tensor containing the scale for audio renormalization. """ assert x.dim() == 3 x, scale = self.preprocess(x)