wip deep_floyd nodes

.gitignore

@@ -8,6 +8,7 @@
 ![Cc]ustom_nodes/__init__.py
 !/custom_nodes/example_node.py.example
 **/put*here
+![Mm]odels/deepfloyd/put_deepfloyd_repos_here
 /extra_model_paths.yaml
 /.vs
 .idea/

comfy_extras/nodes/deepfloyd/deep_floyd.py

@@ -7,7 +7,7 @@ import torch
 import torchvision.transforms.functional as TF
 from diffusers import DiffusionPipeline, IFPipeline, StableDiffusionUpscalePipeline, IFSuperResolutionPipeline
 from diffusers.utils import is_accelerate_available, is_accelerate_version
-from transformers import T5EncoderModel
+from transformers import T5EncoderModel, BitsAndBytesConfig
 
 from comfy.model_management import throw_exception_if_processing_interrupted, get_torch_device, cpu_state, CPUState
 # todo: this relies on the setup-py cleanup fork
@@ -89,8 +89,7 @@ class Loader:
         return {
             "required": {
                 "model_name": (Loader._MODELS, {"default": "I-M"}),
-                "load_in_8bit": ([False, True], {"default": False}),
-                "device": ("STRING", {"default": ""}),
+                "quantization": (list(Loader._QUANTIZATIONS.keys()), {"default": "16-bit"}),
             }
         }
 
@@ -100,8 +99,19 @@ class Loader:
 
     _MODELS = ["I-M", "I-L", "I-XL", "II-M", "II-L", "III", "t5"]
 
+    _QUANTIZATIONS = {
+        "4-bit": BitsAndBytesConfig(
+            load_in_4bit=True,
+            bnb_4bit_use_double_quant=True,
+        ),
+        "8-bit": BitsAndBytesConfig(
+            load_in_8bit=True,
+        ),
+        "16-bit": None,
+    }
+
     # todo: correctly use load_in_8bit
-    def process(self, model_name: str, load_in_8bit: bool, device: str):
+    def process(self, model_name: str, quantization: str):
         assert model_name in Loader._MODELS
 
         model_v: DiffusionPipeline
@@ -113,18 +123,17 @@ class Loader:
             "feature_extractor": None,
             "safety_checker": None,
             "watermarker": None,
-            "load_in_8bit": load_in_8bit,
-            # todo: fix diffusers when using device_map auto on multi-gpu setups, layers are not assigned to different devices correctly
-            "device_map": None if device else "auto"
+            "device_map": None
         }
 
+        if Loader._QUANTIZATIONS[quantization] is not None:
+            kwargs['quantization_config'] = Loader._QUANTIZATIONS[quantization]
+
         if model_name == "t5":
             # find any valid IF model
             model_path = next(os.path.dirname(file) for file in _find_files(_model_base_path, "model_index.json") if
                               any(x == T5EncoderModel.__name__ for x in
                                   json.load(open(file, 'r'))["text_encoder"]))
-            # todo: this must use load_in_8bit correctly
-            # kwargs["text_encoder"] = text_encoder
             kwargs["unet"] = None
         elif model_name == "III":
             model_path = f"{_model_base_path}/stable-diffusion-x4-upscaler"
@@ -138,8 +147,8 @@ class Loader:
             **kwargs
         )
 
-        if device:
-            model_v = model_v.to(device)
+        device = get_torch_device()
+        model_v = model_v.to(device)
 
         _cpu_offload(model_v, gpu_id=model_v.device.index)