1 files changed, 0 insertions, 13 deletions

diff --git a/training/functional.py b/training/functional.py
index 3c7848f..a3d1f08 100644
--- a/training/functional.py
+++ b/training/functional.py
@@ -29,11 +29,8 @@ from pipelines.stable_diffusion.vlpn_stable_diffusion import VlpnStableDiffusion
 from models.clip.embeddings import ManagedCLIPTextEmbeddings
 from models.clip.util import get_extended_embeddings
 from models.clip.tokenizer import MultiCLIPTokenizer
-from models.convnext.discriminator import ConvNeXtDiscriminator
 from training.util import AverageMeter
 from training.sampler import ScheduleSampler, LossAwareSampler, UniformSampler
-from util.slerp import slerp
-from util.noise import perlin_noise
 
 
 def const(result=None):
@@ -349,7 +346,6 @@ def loss_step(
     prior_loss_weight: float,
     seed: int,
     input_pertubation: float,
-    disc: Optional[ConvNeXtDiscriminator],
     min_snr_gamma: int,
     step: int,
     batch: dict[str, Any],
@@ -449,13 +445,6 @@ def loss_step(
 
     loss = loss.mean([1, 2, 3])
 
-    if disc is not None:
-        rec_latent = get_original(noise_scheduler, model_pred, noisy_latents, timesteps)
-        rec_latent = rec_latent / vae.config.scaling_factor
-        rec_latent = rec_latent.to(dtype=vae.dtype)
-        rec = vae.decode(rec_latent, return_dict=False)[0]
-        loss = 1 - disc.get_score(rec)
-
     if min_snr_gamma != 0:
         snr = compute_snr(timesteps, noise_scheduler)
         mse_loss_weights = (
@@ -741,7 +730,6 @@ def train(
     guidance_scale: float = 0.0,
     prior_loss_weight: float = 1.0,
     input_pertubation: float = 0.1,
-    disc: Optional[ConvNeXtDiscriminator] = None,
     schedule_sampler: Optional[ScheduleSampler] = None,
     min_snr_gamma: int = 5,
     avg_loss: AverageMeter = AverageMeter(),
@@ -803,7 +791,6 @@ def train(
         prior_loss_weight,
         seed,
         input_pertubation,
-        disc,
         min_snr_gamma,
     )