allow for prompt audio to be passed in as prime_wave_path to AudioLM

README.md

@@ -342,10 +342,10 @@ $ accelerate launch train.py
 - [x] allow for specialized relative positional embeddings in fine transformer based on absolute matching positions of quantizers between coarse and fine
 - [x] allow for grouped residual vq in soundstream (use `GroupedResidualVQ` from vector-quantize-pytorch lib), from <a href="https://arxiv.org/abs/2305.02765">hifi-codec</a>
 - [x] add flash attention with <a href="https://arxiv.org/abs/2305.19466">NoPE</a>
+- [x] accept prime wave in `AudioLM` as a path to an audio file, and auto resample for semantic vs acoustic
 
 - [ ] design a hierarchical coarse and fine transformer
 - [ ] investigate <a href="https://openreview.net/forum?id=H-VlwsYvVi">spec decoding</a>, first test in x-transformers, then port over if applicable
-- [ ] accept prime wave in `AudioLM` as a path to an audio file, and auto resample for semantic vs acoustic
 
 - [ ] redo the positional embeddings in the presence of groups in residual vq
 - [ ] test with speech synthesis for starters

audiolm_pytorch/audiolm_pytorch.py

@@ -10,6 +10,8 @@
 import torch.nn.functional as F
 from torch.nn.utils.rnn import pad_sequence
 
+import torchaudio
+
 from einops import rearrange, repeat, reduce
 from einops.layers.torch import Rearrange
 
@@ -1901,6 +1903,7 @@ def forward(
         text_embeds: Optional[Tensor] = None,
         prime_wave = None,
         prime_wave_input_sample_hz = None,
+        prime_wave_path = None,
         max_length = 2048,
         return_coarse_generated_wave = False,
         mask_out_generated_fine_tokens = False
@@ -1911,7 +1914,16 @@ def forward(
             if exists(text):
                 text_embeds = self.semantic.embed_text(text)
 
+        assert not (exists(prime_wave) and exists(prime_wave_path)), 'prompt audio must be given as either `prime_wave: Tensor` or `prime_wave_path: str`'
+
         if exists(prime_wave):
+            assert exists(prime_wave_input_sample_hz), 'the input sample frequency for the prompt audio must be given as `prime_wave_input_sample_hz: int`'
+            prime_wave = prime_wave.to(self.device)
+        elif exists(prime_wave_path):
+            prime_wave_path = Path(prime_wave_path)
+            assert exists(prime_wave_path), f'file does not exist at {str(prime_wave_path)}'
+
+            prime_wave, prime_wave_input_sample_hz = torchaudio.load(str(prime_wave_path))
             prime_wave = prime_wave.to(self.device)
 
         semantic_token_ids = self.semantic.generate(

audiolm_pytorch/version.py

@@ -1 +1 @@
-__version__ = '1.2.23'
+__version__ = '1.2.24'