Merge pull request #1082 from bghira/dependency/diffusers-update

update to diffusers v0.31 for SD3.5

helpers/data_backend/factory.py

@@ -561,8 +561,11 @@ def configure_multi_databackend(args: dict, accelerator, text_encoders, tokenize
             raise ValueError("Each dataset needs a unique 'id' field.")
         info_log(f"Configuring data backend: {backend['id']}")
         conditioning_type = backend.get("conditioning_type")
-        if backend.get("dataset_type") == "conditioning" or conditioning_type is not None:
-            backend['dataset_type'] = 'conditioning'
+        if (
+            backend.get("dataset_type") == "conditioning"
+            or conditioning_type is not None
+        ):
+            backend["dataset_type"] = "conditioning"
         resolution_type = backend.get("resolution_type", args.resolution_type)
         if resolution_type == "pixel_area":
             pixel_edge_length = backend.get("resolution", int(args.resolution))
@@ -897,6 +900,7 @@ def configure_multi_databackend(args: dict, accelerator, text_encoders, tokenize
             ),
             instance_prompt=backend.get("instance_prompt", args.instance_prompt),
             conditioning_type=conditioning_type,
+            is_regularisation_data=is_regularisation_data,
         )
         if init_backend["sampler"].caption_strategy == "parquet":
             configure_parquet_database(backend, args, init_backend["data_backend"])

helpers/multiaspect/sampler.py

@@ -39,6 +39,7 @@ def __init__(
         prepend_instance_prompt=False,
         instance_prompt: str = None,
         conditioning_type: str = None,
+        is_regularisation_data: bool = False,
     ):
         """
         Initializes the sampler with provided settings.
@@ -67,6 +68,7 @@ def __init__(
                     f"Unknown conditioning image type: {conditioning_type}"
                 )
         self.conditioning_type = conditioning_type
+        self.is_regularisation_data = is_regularisation_data
 
         self.rank_info = rank_info()
         self.accelerator = accelerator
@@ -377,10 +379,6 @@ def log_state(self, show_rank: bool = True, alt_stats: bool = False):
                 total_image_count *= self.accelerator.num_processes
                 total_image_count = f"~{total_image_count}"
             data_backend_config = StateTracker.get_data_backend_config(self.id)
-            is_regularisation_data = data_backend_config.get(
-                "is_regularisation_data",
-                data_backend_config.get("is_regularization_data", False),
-            )
             printed_state = (
                 f"- Repeats: {data_backend_config.get('repeats', 0)}\n"
                 f"- Total number of images: {total_image_count}\n"
@@ -389,7 +387,7 @@ def log_state(self, show_rank: bool = True, alt_stats: bool = False):
                 f"- Cropped: {data_backend_config.get('crop')}\n"
                 f"- Crop style: {'None' if not data_backend_config.get('crop') else data_backend_config.get('crop_style')}\n"
                 f"- Crop aspect: {'None' if not data_backend_config.get('crop') else data_backend_config.get('crop_aspect')}\n"
-                f"- Used for regularisation data: {'Yes' if is_regularisation_data else 'No'}\n"
+                f"- Used for regularisation data: {'Yes' if self.is_regularisation_data else 'No'}\n"
             )
             if self.conditioning_type:
                 printed_state += f"- Conditioning type: {self.conditioning_type}\n"

install/apple/pyproject.toml

@@ -11,7 +11,7 @@ package-mode = false
 python = ">=3.10,<3.13"
 torch = "^2.5.0"
 torchvision = "^0.20.0"
-diffusers = {git = "https://github.com/huggingface/diffusers", rev = "quantization-config"}
+diffusers = "^0.31.0"
 transformers = "^4.44.2"
 datasets = "^3.0.0"
 wandb = "^0.18.1"

install/rocm/pyproject.toml

@@ -22,7 +22,7 @@ colorama = "^0.4.6"
 compel = "^2"
 datasets = "^3.0.0"
 deepspeed = "^0.15.1"
-diffusers = {git = "https://github.com/huggingface/diffusers", rev = "quantization-config"}
+diffusers = "^0.31.0"
 iterutils = "^0.1.6"
 numpy = "1.26"
 open-clip-torch = "^2.26.1"

pyproject.toml

@@ -11,7 +11,7 @@ package-mode = false
 python = ">=3.10,<3.12"
 torch = {version = "^2.5.0+cu124", source = "pytorch"}
 torchvision = {version = "^0.20.0+cu124", source = "pytorch"}
-diffusers = {git = "https://github.com/huggingface/diffusers", rev = "quantization-config"}
+diffusers = "^0.31.0"
 transformers = "^4.45.1"
 datasets = "^3.0.1"
 bitsandbytes = "^0.44.1"