Merge pull request #3003 from akx/duplicate-code-removal

Duplicate code removal

TTS/tts/layers/tortoise/diffusion.py

@@ -1085,31 +1085,6 @@ class GaussianDiffusion:
         }
 
 
-def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
-    """
-    Get a pre-defined beta schedule for the given name.
-
-    The beta schedule library consists of beta schedules which remain similar
-    in the limit of num_diffusion_timesteps.
-    Beta schedules may be added, but should not be removed or changed once
-    they are committed to maintain backwards compatibility.
-    """
-    if schedule_name == "linear":
-        # Linear schedule from Ho et al, extended to work for any number of
-        # diffusion steps.
-        scale = 1000 / num_diffusion_timesteps
-        beta_start = scale * 0.0001
-        beta_end = scale * 0.02
-        return np.linspace(beta_start, beta_end, num_diffusion_timesteps, dtype=np.float64)
-    elif schedule_name == "cosine":
-        return betas_for_alpha_bar(
-            num_diffusion_timesteps,
-            lambda t: math.cos((t + 0.008) / 1.008 * math.pi / 2) ** 2,
-        )
-    else:
-        raise NotImplementedError(f"unknown beta schedule: {schedule_name}")
-
-
 class SpacedDiffusion(GaussianDiffusion):
     """
     A diffusion process which can skip steps in a base diffusion process.

TTS/tts/layers/xtts/diffusion.py

@@ -1170,31 +1170,6 @@ class GaussianDiffusion:
         }
 
 
-def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
-    """
-    Get a pre-defined beta schedule for the given name.
-
-    The beta schedule library consists of beta schedules which remain similar
-    in the limit of num_diffusion_timesteps.
-    Beta schedules may be added, but should not be removed or changed once
-    they are committed to maintain backwards compatibility.
-    """
-    if schedule_name == "linear":
-        # Linear schedule from Ho et al, extended to work for any number of
-        # diffusion steps.
-        scale = 1000 / num_diffusion_timesteps
-        beta_start = scale * 0.0001
-        beta_end = scale * 0.02
-        return np.linspace(beta_start, beta_end, num_diffusion_timesteps, dtype=np.float64)
-    elif schedule_name == "cosine":
-        return betas_for_alpha_bar(
-            num_diffusion_timesteps,
-            lambda t: math.cos((t + 0.008) / 1.008 * math.pi / 2) ** 2,
-        )
-    else:
-        raise NotImplementedError(f"unknown beta schedule: {schedule_name}")
-
-
 class SpacedDiffusion(GaussianDiffusion):
     """
     A diffusion process which can skip steps in a base diffusion process.

TTS/tts/layers/xtts/tokenizer.py

@@ -171,17 +171,6 @@ def multilingual_cleaners(text, lang):
     return text
 
 
-def english_cleaners(text):
-    """Pipeline for English text, including number and abbreviation expansion."""
-    text = convert_to_ascii(text)
-    text = lowercase(text)
-    text = expand_numbers(text)
-    text = expand_abbreviations(text)
-    text = collapse_whitespace(text)
-    text = text.replace('"', "")
-    return text
-
-
 def remove_extraneous_punctuation(word):
     replacement_punctuation = {"{": "(", "}": ")", "[": "(", "]": ")", "`": "'", "—": "-", "—": "-", "`": "'", "ʼ": "'"}
     replace = re.compile(
@@ -195,32 +184,6 @@ def remove_extraneous_punctuation(word):
     return word
 
 
-def expand_numbers(text):
-    return normalize_numbers(text)
-
-
-def lowercase(text):
-    return text.lower()
-
-
-_whitespace_re = re.compile(r"\s+")
-
-
-def collapse_whitespace(text):
-    return re.sub(_whitespace_re, " ", text)
-
-
-def convert_to_ascii(text):
-    return unidecode(text)
-
-
-def basic_cleaners(text):
-    """Basic pipeline that lowercases and collapses whitespace without transliteration."""
-    text = lowercase(text)
-    text = collapse_whitespace(text)
-    return text
-
-
 def arabic_cleaners(text):
     text = lowercase(text)
     text = collapse_whitespace(text)

TTS/tts/models/delightful_tts.py

@@ -726,8 +726,8 @@ class DelightfulTTS(BaseTTSE2E):
     def pitch_std(self):
         return self.acoustic_model.pitch_std
 
-    @pitch_mean.setter
+    @pitch_std.setter
-    def pitch_std(self, value):  # pylint: disable=function-redefined
+    def pitch_std(self, value):
         self.acoustic_model.pitch_std = value
 
     @property
@@ -1518,10 +1518,6 @@ class DelightfulTTS(BaseTTSE2E):
         scheduler_G = get_scheduler(self.config.lr_scheduler_disc, self.config.lr_scheduler_disc_params, optimizer[1])
         return [scheduler_D, scheduler_G]
 
-    def on_train_step_start(self, trainer):
-        """Schedule binary loss weight."""
-        self.binary_loss_weight = min(trainer.epochs_done / self.config.binary_loss_warmup_epochs, 1.0) * 1.0
-
     def on_epoch_end(self, trainer):  # pylint: disable=unused-argument
         # stop updating mean and var
         # TODO: do the same for F0
@@ -1578,6 +1574,7 @@ class DelightfulTTS(BaseTTSE2E):
         Args:
             trainer (Trainer): Trainer object.
         """
+        self.binary_loss_weight = min(trainer.epochs_done / self.config.binary_loss_warmup_epochs, 1.0) * 1.0
         self.train_disc = (  # pylint: disable=attribute-defined-outside-init
             trainer.total_steps_done >= self.config.steps_to_start_discriminator
         )

TTS/vc/modules/freevc/commons.py

@@ -116,12 +116,6 @@ def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
     return acts
 
 
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
 def shift_1d(x):
     x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
     return x