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update

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This commit is contained in:
Dhruv Nair
2023-12-29 14:38:32 +00:00
parent b791a713e5
commit c6c8fc7fde
2 changed files with 12 additions and 15 deletions
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6
src/diffusers/loaders/single_file.py
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@@ -199,12 +199,6 @@ def build_additional_components(
)
return stable_unclip_components
if pipeline_class_name == "LDMTextToImagePipeline":
ldm_text_to_image_components = create_ldm_text_to_image_components(
pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, **kwargs
)
return ldm_text_to_image_components
if pipeline_class_name == "PaintByExamplePipeline":
paint_by_example_components = create_paint_by_example_components(
pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, **kwargs

21
src/diffusers/loaders/single_file_utils.py
View File

@@ -237,12 +237,13 @@ def determine_image_size(pipeline_class_name, original_config, checkpoint, **kwa
"parameterization" in original_config["model"]["params"]
and original_config["model"]["params"]["parameterization"] == "v"
):
# NOTE: For stable diffusion 2 base one has to pass `image_size==512`
# as it relies on a brittle global step parameter here
image_size = 512 if global_step == 875000 else 768
# NOTE: For stable diffusion 2 base one has to pass `image_size==512`
# as it relies on a brittle global step parameter here
image_size = 512 if global_step == 875000 else 768
return image_size
def shave_segments(path, n_shave_prefix_segments=1):
"""
Removes segments. Positive values shave the first segments, negative shave the last segments.
@@ -1315,7 +1316,9 @@ def create_unet_model(pipeline_class_name, original_config, checkpoint, checkpoi
return {"unet": unet}
def create_controlnet_model(pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, image_size, **kwargs):
def create_controlnet_model(
pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, image_size, **kwargs
):
if "control_stage_config" not in original_config.model.params:
raise ValueError("Config does not have controlnet information")
@@ -1349,7 +1352,9 @@ def create_vae_model(pipeline_class_name, original_config, checkpoint, checkpoin
return {"vae": vae}
def create_text_encoders_and_tokenizers(pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, **kwargs):
def create_text_encoders_and_tokenizers(
pipeline_class_name, original_config, checkpoint, checkpoint_path_or_dict, **kwargs
):
model_type = infer_model_type(pipeline_class_name, original_config)
local_files_only = kwargs.get("local_files_only", False)
@@ -1450,7 +1455,7 @@ def create_text_encoders_and_tokenizers(pipeline_class_name, original_config, ch
"text_encoder_2": text_encoder_2,
}
elif model_type == "LDMText2Image":
elif pipeline_class_name == "LDMTextToImagePipeline":
text_config = create_ldm_bert_config(original_config)
text_encoder = convert_ldm_bert_checkpoint(checkpoint, text_config)
tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased", local_files_only=local_files_only)
@@ -1525,9 +1530,7 @@ def create_scheduler(pipeline_class_name, original_config, checkpoint, checkpoin
raise ValueError(f"Scheduler of type {scheduler_type} doesn't exist!")
if pipeline_class_name == "StableDiffusionUpscalePipeline":
scheduler = DDIMScheduler.from_pretrained(
"stabilityai/stable-diffusion-x4-upscaler", subfolder="scheduler"
)
scheduler = DDIMScheduler.from_pretrained("stabilityai/stable-diffusion-x4-upscaler", subfolder="scheduler")
low_res_scheduler = DDPMScheduler.from_pretrained(
"stabilityai/stable-diffusion-x4-upscaler", subfolder="low_res_scheduler"
)