From 705551c60c84ff8856efc3cf428ecf817a4f7f72 Mon Sep 17 00:00:00 2001 From: Enno Hermann Date: Thu, 21 Nov 2024 12:40:12 +0100 Subject: [PATCH] refactor(tortoise): remove unused do_checkpoint arguments These are assigned but not used for anything. --- TTS/tts/layers/tortoise/arch_utils.py | 2 -- TTS/tts/layers/tortoise/autoregressive.py | 2 -- TTS/tts/layers/tortoise/classifier.py | 6 ++---- TTS/tts/layers/tortoise/diffusion_decoder.py | 5 ----- 4 files changed, 2 insertions(+), 13 deletions(-) diff --git a/TTS/tts/layers/tortoise/arch_utils.py b/TTS/tts/layers/tortoise/arch_utils.py index c9abcf60..4c3733e6 100644 --- a/TTS/tts/layers/tortoise/arch_utils.py +++ b/TTS/tts/layers/tortoise/arch_utils.py @@ -93,12 +93,10 @@ class AttentionBlock(nn.Module): channels, num_heads=1, num_head_channels=-1, - do_checkpoint=True, relative_pos_embeddings=False, ): super().__init__() self.channels = channels - self.do_checkpoint = do_checkpoint if num_head_channels == -1: self.num_heads = num_heads else: diff --git a/TTS/tts/layers/tortoise/autoregressive.py b/TTS/tts/layers/tortoise/autoregressive.py index aaae6955..e3ffd4d1 100644 --- a/TTS/tts/layers/tortoise/autoregressive.py +++ b/TTS/tts/layers/tortoise/autoregressive.py @@ -175,7 +175,6 @@ class ConditioningEncoder(nn.Module): embedding_dim, attn_blocks=6, num_attn_heads=4, - do_checkpointing=False, mean=False, ): super().__init__() @@ -185,7 +184,6 @@ class ConditioningEncoder(nn.Module): attn.append(AttentionBlock(embedding_dim, num_attn_heads)) self.attn = nn.Sequential(*attn) self.dim = embedding_dim - self.do_checkpointing = do_checkpointing self.mean = mean def forward(self, x): diff --git a/TTS/tts/layers/tortoise/classifier.py b/TTS/tts/layers/tortoise/classifier.py index 8764bb07..c72834e9 100644 --- a/TTS/tts/layers/tortoise/classifier.py +++ b/TTS/tts/layers/tortoise/classifier.py @@ -16,7 +16,6 @@ class ResBlock(nn.Module): up=False, down=False, kernel_size=3, - do_checkpoint=True, ): super().__init__() self.channels = channels @@ -24,7 +23,6 @@ class ResBlock(nn.Module): self.out_channels = out_channels or channels self.use_conv = use_conv self.use_scale_shift_norm = use_scale_shift_norm - self.do_checkpoint = do_checkpoint padding = 1 if kernel_size == 3 else 2 self.in_layers = nn.Sequential( @@ -92,14 +90,14 @@ class AudioMiniEncoder(nn.Module): self.layers = depth for l in range(depth): for r in range(resnet_blocks): - res.append(ResBlock(ch, dropout, do_checkpoint=False, kernel_size=kernel_size)) + res.append(ResBlock(ch, dropout, kernel_size=kernel_size)) res.append(Downsample(ch, use_conv=True, out_channels=ch * 2, factor=downsample_factor)) ch *= 2 self.res = nn.Sequential(*res) self.final = nn.Sequential(normalization(ch), nn.SiLU(), nn.Conv1d(ch, embedding_dim, 1)) attn = [] for a in range(attn_blocks): - attn.append(AttentionBlock(embedding_dim, num_attn_heads, do_checkpoint=False)) + attn.append(AttentionBlock(embedding_dim, num_attn_heads)) self.attn = nn.Sequential(*attn) self.dim = embedding_dim diff --git a/TTS/tts/layers/tortoise/diffusion_decoder.py b/TTS/tts/layers/tortoise/diffusion_decoder.py index f71eaf17..15bbfb71 100644 --- a/TTS/tts/layers/tortoise/diffusion_decoder.py +++ b/TTS/tts/layers/tortoise/diffusion_decoder.py @@ -196,31 +196,26 @@ class DiffusionTts(nn.Module): model_channels * 2, num_heads, relative_pos_embeddings=True, - do_checkpoint=False, ), AttentionBlock( model_channels * 2, num_heads, relative_pos_embeddings=True, - do_checkpoint=False, ), AttentionBlock( model_channels * 2, num_heads, relative_pos_embeddings=True, - do_checkpoint=False, ), AttentionBlock( model_channels * 2, num_heads, relative_pos_embeddings=True, - do_checkpoint=False, ), AttentionBlock( model_channels * 2, num_heads, relative_pos_embeddings=True, - do_checkpoint=False, ), ) self.unconditioned_embedding = nn.Parameter(torch.randn(1, model_channels, 1))