From 95f627d99157790a48cd2d4ace93bce25085cbe9 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Sun, 9 Jun 2024 15:37:32 +0900 Subject: [PATCH] chore(format): run black on dev (#13) Co-authored-by: github-actions[bot] --- infer/lib/infer_pack/models.py | 4 ++-- infer/lib/train/utils.py | 2 +- rvc/attentions.py | 1 + rvc/encoders.py | 1 + rvc/generators.py | 13 +++++++++---- rvc/nsf.py | 3 ++- 6 files changed, 16 insertions(+), 8 deletions(-) diff --git a/infer/lib/infer_pack/models.py b/infer/lib/infer_pack/models.py index e31c65e..52ab241 100644 --- a/infer/lib/infer_pack/models.py +++ b/infer/lib/infer_pack/models.py @@ -309,7 +309,7 @@ class SynthesizerTrnMs256NSFsid_nono(nn.Module): upsample_kernel_sizes: List[int], spk_embed_dim: int, gin_channels: int, - sr = None, + sr=None, ): super(SynthesizerTrnMs256NSFsid_nono, self).__init__() self.spec_channels = spec_channels @@ -464,7 +464,7 @@ class SynthesizerTrnMs768NSFsid_nono(SynthesizerTrnMs256NSFsid_nono): upsample_kernel_sizes: List[int], spk_embed_dim: int, gin_channels: int, - sr = None, + sr=None, ): super(SynthesizerTrnMs768NSFsid_nono, self).__init__( spec_channels, diff --git a/infer/lib/train/utils.py b/infer/lib/train/utils.py index 2467333..bfffcd7 100644 --- a/infer/lib/train/utils.py +++ b/infer/lib/train/utils.py @@ -256,7 +256,7 @@ def load_filepaths_and_text(filename, split="|"): except UnicodeDecodeError: with open(filename) as f: filepaths_and_text = [line.strip().split(split) for line in f] - + return filepaths_and_text diff --git a/rvc/attentions.py b/rvc/attentions.py index 94c4278..22b626d 100644 --- a/rvc/attentions.py +++ b/rvc/attentions.py @@ -229,6 +229,7 @@ class FFN(nn.Module): """ Feed-Forward Network """ + def __init__( self, in_channels: int, diff --git a/rvc/encoders.py b/rvc/encoders.py index 147118f..7dd3f7f 100644 --- a/rvc/encoders.py +++ b/rvc/encoders.py @@ -161,6 +161,7 @@ class TextEncoder(nn.Module): m, logs = torch.split(stats, self.out_channels, dim=1) return m, logs, x_mask + class PosteriorEncoder(nn.Module): def __init__( self, diff --git a/rvc/generators.py b/rvc/generators.py index e9229d6..9815338 100644 --- a/rvc/generators.py +++ b/rvc/generators.py @@ -9,6 +9,7 @@ from torch.nn.utils import remove_weight_norm, weight_norm from .residuals import ResBlock1, ResBlock2, LRELU_SLOPE from .utils import call_weight_data_normal_if_Conv + class Generator(torch.nn.Module): def __init__( self, @@ -156,11 +157,15 @@ class SineGenerator(torch.nn.Module): self.dim = harmonic_num + 1 self.sampling_rate = samp_rate self.voiced_threshold = voiced_threshold - - def __call__(self, f0: torch.Tensor, upp: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: + + def __call__( + self, f0: torch.Tensor, upp: int + ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: return super().__call__(f0, upp) - def forward(self, f0: torch.Tensor, upp: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: + def forward( + self, f0: torch.Tensor, upp: int + ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: """sine_tensor, uv = forward(f0) input F0: tensor(batchsize=1, length, dim=1) f0 for unvoiced steps should be 0 @@ -190,7 +195,7 @@ class SineGenerator(torch.nn.Module): tmp_over_one *= upp tmp_over_one: torch.Tensor = F.interpolate( tmp_over_one.transpose(2, 1), - scale_factor = float(upp), + scale_factor=float(upp), mode="linear", align_corners=True, ).transpose(2, 1) diff --git a/rvc/nsf.py b/rvc/nsf.py index 6842dd7..9e75cb0 100644 --- a/rvc/nsf.py +++ b/rvc/nsf.py @@ -57,7 +57,8 @@ class SourceModuleHnNSF(torch.nn.Module): sine_wavs, _, _ = self.l_sin_gen(x, upp) sine_wavs = sine_wavs.to(dtype=self.l_linear.weight.dtype) sine_merge: torch.Tensor = self.l_tanh(self.l_linear(sine_wavs)) - return sine_merge #, None, None # noise, uv + return sine_merge # , None, None # noise, uv + class NSFGenerator(torch.nn.Module): def __init__(