Remove duplicate get_named_beta_schedules

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.