This is not needed.

comfy_extras/nodes_audio.py

@@ -288,7 +288,7 @@ def f32_pcm(wav: torch.Tensor) -> torch.Tensor:
         return wav.float() / (2 ** 31)
     raise ValueError(f"Unsupported wav dtype: {wav.dtype}")
 
-def load(filepath: str, frame_offset: int = 0, num_frames: int = -1) -> tuple[torch.Tensor, int]:
+def load(filepath: str) -> tuple[torch.Tensor, int]:
     with av.open(filepath) as af:
         if not af.streams.audio:
             raise ValueError("No audio stream found in the file.")
@@ -297,40 +297,20 @@ def load(filepath: str, frame_offset: int = 0, num_frames: int = -1) -> tuple[to
         sr = stream.codec_context.sample_rate
         n_channels = stream.channels
 
-        seek_time = frame_offset / sr if frame_offset > 0 else 0.0
-        duration = num_frames / sr if num_frames > 0 else -1.0
-
-        sample_offset = int(sr * seek_time)
-        num_samples = int(sr * duration) if duration >= 0 else -1
-
-        # Small negative offset for MP3 artifacts, NOTE: this is LLM code so idk if it's actually necessary'
-        seek_sec = max(0, seek_time - 0.1) if filepath.lower().endswith('.mp3') else seek_time
-        af.seek(int(seek_sec / stream.time_base), stream=stream)
-
         frames = []
         length = 0
         for frame in af.decode(streams=stream.index):
-            current_offset = int(frame.rate * frame.pts * frame.time_base)
-            strip = max(0, sample_offset - current_offset)
-
             buf = torch.from_numpy(frame.to_ndarray())
             if buf.shape[0] != n_channels:
                 buf = buf.view(-1, n_channels).t()
 
-            buf = buf[:, strip:]
             frames.append(buf)
             length += buf.shape[1]
 
-            if num_samples > 0 and length >= num_samples:
-                break
-
         if not frames:
             raise ValueError("No audio frames decoded.")
 
         wav = torch.cat(frames, dim=1)
-        if num_samples > 0:
-            wav = wav[:, :num_samples]
-
         wav = f32_pcm(wav)
         return wav, sr