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[SDXL ControlNet Training] Follow-up fixes (#4188)

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* hash computation. thanks to @lhoestq

* disable dtype casting.

* remove comments.
This commit is contained in:
Sayak Paul
2023-07-21 20:55:33 +05:30
committed by GitHub
parent aed30dff6b
commit 4dcab9227a
1 changed files with 6 additions and 3 deletions
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9
examples/controlnet/train_controlnet_sdxl.py
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@@ -1001,7 +1001,12 @@ def main(args):
proportion_empty_prompts=args.proportion_empty_prompts,
)
with accelerator.main_process_first():
train_dataset = train_dataset.map(compute_embeddings_fn, batched=True)
from datasets.fingerprint import Hasher
# fingerprint used by the cache for the other processes to load the result
# details: https://github.com/huggingface/diffusers/pull/4038#discussion_r1266078401
new_fingerprint = Hasher.hash(args)
train_dataset = train_dataset.map(compute_embeddings_fn, batched=True, new_fingerprint=new_fingerprint)
del text_encoders, tokenizers
gc.collect()
@@ -1113,8 +1118,6 @@ def main(args):
# Convert images to latent space
if args.pretrained_vae_model_name_or_path is not None:
pixel_values = batch["pixel_values"].to(dtype=weight_dtype)
if vae.dtype != weight_dtype:
vae.to(dtype=weight_dtype)
else:
pixel_values = batch["pixel_values"]
latents = vae.encode(pixel_values).latent_dist.sample()