From 427ad7997495dedd1dd2185e4368f3849d814a7c Mon Sep 17 00:00:00 2001
From: tarepan <tarepan5884@gmail.com>
Date: Sun, 23 Apr 2023 13:20:53 +0000
Subject: [PATCH] Refactor wave-to-mel

---
 train/mel_processing.py | 62 +++--------------------------------------
 1 file changed, 4 insertions(+), 58 deletions(-)

diff --git a/train/mel_processing.py b/train/mel_processing.py
index 315b3d1..821eb27 100644
--- a/train/mel_processing.py
+++ b/train/mel_processing.py
@@ -100,61 +100,7 @@ def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
     return spec
 
 
-def mel_spectrogram_torch(
-    y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False
-):
-    if torch.min(y) < -1.0:
-        print("min value is ", torch.min(y))
-    if torch.max(y) > 1.0:
-        print("max value is ", torch.max(y))
-
-    global mel_basis, hann_window
-    dtype_device = str(y.dtype) + "_" + str(y.device)
-    fmax_dtype_device = str(fmax) + "_" + dtype_device
-    wnsize_dtype_device = str(win_size) + "_" + dtype_device
-    if fmax_dtype_device not in mel_basis:
-        mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
-        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(
-            dtype=y.dtype, device=y.device
-        )
-    if wnsize_dtype_device not in hann_window:
-        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(
-            dtype=y.dtype, device=y.device
-        )
-
-    y = torch.nn.functional.pad(
-        y.unsqueeze(1),
-        (int((n_fft - hop_size) / 2), int((n_fft - hop_size) / 2)),
-        mode="reflect",
-    )
-    y = y.squeeze(1)
-
-    # spec = torch.stft(
-    #     y,
-    #     n_fft,
-    #     hop_length=hop_size,
-    #     win_length=win_size,
-    #     window=hann_window[wnsize_dtype_device],
-    #     center=center,
-    #     pad_mode="reflect",
-    #     normalized=False,
-    #     onesided=True,
-    # )
-    spec = torch.stft(
-        y,
-        n_fft,
-        hop_length=hop_size,
-        win_length=win_size,
-        window=hann_window[wnsize_dtype_device],
-        center=center,
-        pad_mode="reflect",
-        normalized=False,
-        onesided=True,
-        return_complex=False,
-    )
-    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
-
-    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
-    spec = spectral_normalize_torch(spec)
-
-    return spec
+def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False):
+    spec = spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center)
+    melspec = spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax)
+    return melspec
\ No newline at end of file