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More guidance work. Improved LoRA module resolver for unet. Added vega mappings and LoRA training for it. Various other bigfixes and changes

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This commit is contained in:
Jaret Burkett
2023-12-15 06:02:10 -07:00
parent e5177833b2
commit 39870411d8
14 changed files with 3501 additions and 106 deletions
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6
toolkit/config_modules.py
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@@ -247,6 +247,7 @@ class ModelConfig:
self.is_v2: bool = kwargs.get('is_v2', False)
self.is_xl: bool = kwargs.get('is_xl', False)
self.is_ssd: bool = kwargs.get('is_ssd', False)
self.is_vega: bool = kwargs.get('is_vega', False)
self.is_v_pred: bool = kwargs.get('is_v_pred', False)
self.dtype: str = kwargs.get('dtype', 'float16')
self.vae_path = kwargs.get('vae_path', None)
@@ -267,6 +268,9 @@ class ModelConfig:
# sed sdxl as true since it is mostly the same architecture
self.is_xl = True
if self.is_vega:
self.is_xl = True
class ReferenceDatasetConfig:
def __init__(self, **kwargs):
@@ -402,7 +406,7 @@ class DatasetConfig:
if legacy_caption_type:
self.caption_ext = legacy_caption_type
self.caption_type = self.caption_ext
self.guidance_type: GuidanceType = kwargs.get('guidance_type', 'targeted_polarity')
self.guidance_type: GuidanceType = kwargs.get('guidance_type', 'targeted')
def preprocess_dataset_raw_config(raw_config: List[dict]) -> List[dict]: