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| author | Volpeon <git@volpeon.ink> | 2022-10-03 12:08:16 +0200 |
|---|---|---|
| committer | Volpeon <git@volpeon.ink> | 2022-10-03 12:08:16 +0200 |
| commit | 6c072fe50b3bfc561f22e5d591212d30de3c2dd2 (patch) | |
| tree | e6dd60b5fa696d614ccc1cddb869c12c29f6ab46 /textual_inversion.py | |
| parent | Assign unused images in validation dataset to train dataset (diff) | |
| download | textual-inversion-diff-6c072fe50b3bfc561f22e5d591212d30de3c2dd2.tar.gz textual-inversion-diff-6c072fe50b3bfc561f22e5d591212d30de3c2dd2.tar.bz2 textual-inversion-diff-6c072fe50b3bfc561f22e5d591212d30de3c2dd2.zip | |
Fixed euler_a generator argument
Diffstat (limited to 'textual_inversion.py')
| -rw-r--r-- | textual_inversion.py | 8 |
1 files changed, 0 insertions, 8 deletions
diff --git a/textual_inversion.py b/textual_inversion.py index fa6214e..285aa0a 100644 --- a/textual_inversion.py +++ b/textual_inversion.py | |||
| @@ -403,8 +403,6 @@ class Checkpointer: | |||
| 403 | prompt = [prompt for i, batch in data_enum for j, prompt in enumerate( | 403 | prompt = [prompt for i, batch in data_enum for j, prompt in enumerate( |
| 404 | batch["prompts"]) if i * val_data.batch_size + j < self.sample_batch_size] | 404 | batch["prompts"]) if i * val_data.batch_size + j < self.sample_batch_size] |
| 405 | 405 | ||
| 406 | generator = torch.Generator(device="cuda").manual_seed(self.seed + i) | ||
| 407 | |||
| 408 | with self.accelerator.autocast(): | 406 | with self.accelerator.autocast(): |
| 409 | samples = pipeline( | 407 | samples = pipeline( |
| 410 | prompt=prompt, | 408 | prompt=prompt, |
| @@ -414,13 +412,11 @@ class Checkpointer: | |||
| 414 | guidance_scale=guidance_scale, | 412 | guidance_scale=guidance_scale, |
| 415 | eta=eta, | 413 | eta=eta, |
| 416 | num_inference_steps=num_inference_steps, | 414 | num_inference_steps=num_inference_steps, |
| 417 | generator=generator, | ||
| 418 | output_type='pil' | 415 | output_type='pil' |
| 419 | )["sample"] | 416 | )["sample"] |
| 420 | 417 | ||
| 421 | all_samples += samples | 418 | all_samples += samples |
| 422 | 419 | ||
| 423 | del generator | ||
| 424 | del samples | 420 | del samples |
| 425 | 421 | ||
| 426 | image_grid = make_grid(all_samples, self.stable_sample_batches, self.sample_batch_size) | 422 | image_grid = make_grid(all_samples, self.stable_sample_batches, self.sample_batch_size) |
| @@ -441,8 +437,6 @@ class Checkpointer: | |||
| 441 | prompt = [prompt for i, batch in data_enum for j, prompt in enumerate( | 437 | prompt = [prompt for i, batch in data_enum for j, prompt in enumerate( |
| 442 | batch["prompts"]) if i * data.batch_size + j < self.sample_batch_size] | 438 | batch["prompts"]) if i * data.batch_size + j < self.sample_batch_size] |
| 443 | 439 | ||
| 444 | generator = torch.Generator(device="cuda").manual_seed(self.seed + i) | ||
| 445 | |||
| 446 | with self.accelerator.autocast(): | 440 | with self.accelerator.autocast(): |
| 447 | samples = pipeline( | 441 | samples = pipeline( |
| 448 | prompt=prompt, | 442 | prompt=prompt, |
| @@ -451,13 +445,11 @@ class Checkpointer: | |||
| 451 | guidance_scale=guidance_scale, | 445 | guidance_scale=guidance_scale, |
| 452 | eta=eta, | 446 | eta=eta, |
| 453 | num_inference_steps=num_inference_steps, | 447 | num_inference_steps=num_inference_steps, |
| 454 | generator=generator, | ||
| 455 | output_type='pil' | 448 | output_type='pil' |
| 456 | )["sample"] | 449 | )["sample"] |
| 457 | 450 | ||
| 458 | all_samples += samples | 451 | all_samples += samples |
| 459 | 452 | ||
| 460 | del generator | ||
| 461 | del samples | 453 | del samples |
| 462 | 454 | ||
| 463 | image_grid = make_grid(all_samples, self.random_sample_batches, self.sample_batch_size) | 455 | image_grid = make_grid(all_samples, self.random_sample_batches, self.sample_batch_size) |