1 files changed, 0 insertions, 8 deletions

diff --git a/dreambooth.py b/dreambooth.py
index 88cd0da..75602dc 100644
--- a/dreambooth.py
+++ b/dreambooth.py
@@ -414,8 +414,6 @@ class Checkpointer:
                 prompt = [prompt for i, batch in data_enum for j, prompt in enumerate(
                     batch["prompts"]) if i * val_data.batch_size + j < self.sample_batch_size]
 
-                generator = torch.Generator(device="cuda").manual_seed(self.seed + i)
-
                 with self.accelerator.autocast():
                     samples = pipeline(
                         prompt=prompt,
@@ -425,13 +423,11 @@ class Checkpointer:
                         guidance_scale=guidance_scale,
                         eta=eta,
                         num_inference_steps=num_inference_steps,
-                        generator=generator,
                         output_type='pil'
                     )["sample"]
 
                 all_samples += samples
 
-                del generator
                 del samples
 
             image_grid = make_grid(all_samples, self.stable_sample_batches, self.sample_batch_size)
@@ -452,8 +448,6 @@ class Checkpointer:
                 prompt = [prompt for i, batch in data_enum for j, prompt in enumerate(
                     batch["prompts"]) if i * data.batch_size + j < self.sample_batch_size]
 
-                generator = torch.Generator(device="cuda").manual_seed(self.seed + i)
-
                 with self.accelerator.autocast():
                     samples = pipeline(
                         prompt=prompt,
@@ -462,13 +456,11 @@ class Checkpointer:
                         guidance_scale=guidance_scale,
                         eta=eta,
                         num_inference_steps=num_inference_steps,
-                        generator=generator,
                         output_type='pil'
                     )["sample"]
 
                 all_samples += samples
 
-                del generator
                 del samples
 
             image_grid = make_grid(all_samples, self.random_sample_batches, self.sample_batch_size)