From d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99 Mon Sep 17 00:00:00 2001
From: liugz18 <57401541+liugz18@users.noreply.github.com>
Date: 星期四, 18 七月 2024 21:34:55 +0800
Subject: [PATCH] Rename 'res' in line 514 to avoid with naming conflict with line 365
---
funasr/frontends/whisper_frontend.py | 65 ++++++++++++++++++++------------
1 files changed, 40 insertions(+), 25 deletions(-)
diff --git a/funasr/frontends/whisper_frontend.py b/funasr/frontends/whisper_frontend.py
index 752fd20..1bd8aec 100644
--- a/funasr/frontends/whisper_frontend.py
+++ b/funasr/frontends/whisper_frontend.py
@@ -1,8 +1,8 @@
from typing import Tuple
import torch
import torch.nn as nn
-import whisper
-from whisper.audio import HOP_LENGTH, N_FFT, N_SAMPLES
+
+
from funasr.register import tables
from torch.nn.utils.rnn import pad_sequence
@@ -15,50 +15,62 @@
"""
def __init__(
- self,
- fs: int = 16000,
- whisper_model: str = "large-v3",
- do_pad_trim: bool = True,
+ self,
+ fs: int = 16000,
+ whisper_model: str = None,
+ do_pad_trim: bool = True,
+ n_mels: int = 80,
+ permute: bool = False,
+ **kwargs,
):
super().__init__()
assert fs == 16000
self.fs = fs
+ import whisper
+ from whisper.audio import HOP_LENGTH, N_FFT, N_SAMPLES
self.n_fft = N_FFT
self.win_length = N_FFT
self.hop_length = HOP_LENGTH
self.pad_samples = N_SAMPLES
- self.frame_shift = self.hop_length
+ self.frame_shift = int(self.hop_length / self.fs * 1000)
self.lfr_n = 1
+ self.n_mels = n_mels
if whisper_model == "large-v3" or whisper_model == "large":
self.n_mels = 128
- else:
- self.n_mels = 80
- self.mel_filters = whisper.audio.mel_filters
+ filters_path = kwargs.get("filters_path", None)
+ self.filters_path = filters_path
+ if filters_path is not None:
+ from funasr.models.sense_voice.whisper_lib.audio import mel_filters
+
+ self.mel_filters = mel_filters
+ else:
+ self.mel_filters = whisper.audio.mel_filters
self.do_pad_trim = do_pad_trim
if do_pad_trim:
self.pad_or_trim = whisper.pad_or_trim
+ self.permute = permute
- assert whisper_model in whisper.available_models()
+ # assert whisper_model in whisper.available_models()
def output_size(self) -> int:
return self.n_mels
def log_mel_spectrogram(
- self,
- audio: torch.Tensor,
- ilens: torch.Tensor = None,
+ self,
+ audio: torch.Tensor,
+ ilens: torch.Tensor = None,
) -> torch.Tensor:
window = torch.hann_window(self.win_length).to(audio.device)
- stft = torch.stft(
- audio, self.n_fft, self.hop_length, window=window, return_complex=True
- )
+ stft = torch.stft(audio, self.n_fft, self.hop_length, window=window, return_complex=True)
# whisper deletes the last frame by default (Shih-Lun)
magnitudes = stft[..., :-1].abs() ** 2
-
- filters = self.mel_filters(audio.device, self.n_mels)
+ if self.filters_path is not None:
+ filters = self.mel_filters(audio.device, self.n_mels, self.filters_path)
+ else:
+ filters = self.mel_filters(audio.device, self.n_mels)
mel_spec = filters @ magnitudes
log_spec = torch.clamp(mel_spec, min=1e-10).log10()
@@ -77,11 +89,15 @@
return log_spec, olens
def forward(
- self, input: torch.Tensor, input_lengths: torch.Tensor
+ self,
+ input: torch.Tensor,
+ input_lengths: torch.Tensor,
+ **kwargs,
) -> Tuple[torch.Tensor, torch.Tensor]:
batch_size = input.size(0)
feats = []
feats_lens = []
+ input = input.to(torch.float32)
for i in range(batch_size):
if self.do_pad_trim:
feat = self.pad_or_trim(input[i], self.pad_samples)
@@ -95,8 +111,7 @@
if batch_size == 1:
feats_pad = feats[0][None, :, :]
else:
- feats_pad = pad_sequence(feats,
- batch_first=True,
- padding_value=0.0)
-
- return feats_pad, feats_lens
\ No newline at end of file
+ feats_pad = pad_sequence(feats, batch_first=True, padding_value=0.0)
+ if self.permute:
+ feats_pad = feats_pad.permute(0, 2, 1)
+ return feats_pad, feats_lens
--
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