Merge branch 'comfyanonymous:master' into master

.ci/windows_base_files/README_VERY_IMPORTANT.txt

@@ -14,7 +14,7 @@ run_cpu.bat
 
 IF YOU GET A RED ERROR IN THE UI MAKE SURE YOU HAVE A MODEL/CHECKPOINT IN: ComfyUI\models\checkpoints
 
-You can download the stable diffusion 1.5 one from: https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt
+You can download the stable diffusion 1.5 one from: https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors
 
 
 RECOMMENDED WAY TO UPDATE:

comfy/controlnet.py

@@ -444,7 +444,12 @@ def load_controlnet_flux_instantx(sd):
     for k in sd:
         new_sd[k] = sd[k]
 
-    control_model = comfy.ldm.flux.controlnet.ControlNetFlux(latent_input=True, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
+    num_union_modes = 0
+    union_cnet = "controlnet_mode_embedder.weight"
+    if union_cnet in new_sd:
+        num_union_modes = new_sd[union_cnet].shape[0]
+
+    control_model = comfy.ldm.flux.controlnet.ControlNetFlux(latent_input=True, num_union_modes=num_union_modes, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
     control_model = controlnet_load_state_dict(control_model, new_sd)
 
     latent_format = comfy.latent_formats.Flux()

comfy/ldm/flux/controlnet.py

@@ -14,7 +14,7 @@ import comfy.ldm.common_dit
 
 
 class ControlNetFlux(Flux):
-    def __init__(self, latent_input=False, image_model=None, dtype=None, device=None, operations=None, **kwargs):
+    def __init__(self, latent_input=False, num_union_modes=0, image_model=None, dtype=None, device=None, operations=None, **kwargs):
         super().__init__(final_layer=False, dtype=dtype, device=device, operations=operations, **kwargs)
 
         self.main_model_double = 19
@@ -29,6 +29,11 @@ class ControlNetFlux(Flux):
         for _ in range(self.params.depth_single_blocks):
             self.controlnet_single_blocks.append(operations.Linear(self.hidden_size, self.hidden_size, dtype=dtype, device=device))
 
+        self.num_union_modes = num_union_modes
+        self.controlnet_mode_embedder = None
+        if self.num_union_modes > 0:
+            self.controlnet_mode_embedder = operations.Embedding(self.num_union_modes, self.hidden_size, dtype=dtype, device=device)
+
         self.gradient_checkpointing = False
         self.latent_input = latent_input
         self.pos_embed_input = operations.Linear(self.in_channels, self.hidden_size, bias=True, dtype=dtype, device=device)
@@ -61,6 +66,7 @@ class ControlNetFlux(Flux):
         timesteps: Tensor,
         y: Tensor,
         guidance: Tensor = None,
+        control_type: Tensor = None,
     ) -> Tensor:
         if img.ndim != 3 or txt.ndim != 3:
             raise ValueError("Input img and txt tensors must have 3 dimensions.")
@@ -79,6 +85,11 @@ class ControlNetFlux(Flux):
         vec = vec + self.vector_in(y)
         txt = self.txt_in(txt)
 
+        if self.controlnet_mode_embedder is not None and len(control_type) > 0:
+            control_cond = self.controlnet_mode_embedder(torch.tensor(control_type, device=img.device), out_dtype=img.dtype).unsqueeze(0).repeat((txt.shape[0], 1, 1))
+            txt = torch.cat([control_cond, txt], dim=1)
+            txt_ids = torch.cat([txt_ids[:,:1], txt_ids], dim=1)
+
         ids = torch.cat((txt_ids, img_ids), dim=1)
         pe = self.pe_embedder(ids)
 
@@ -137,4 +148,4 @@ class ControlNetFlux(Flux):
         img_ids = repeat(img_ids, "h w c -> b (h w) c", b=bs)
 
         txt_ids = torch.zeros((bs, context.shape[1], 3), device=x.device, dtype=x.dtype)
-        return self.forward_orig(img, img_ids, hint, context, txt_ids, timesteps, y, guidance)
+        return self.forward_orig(img, img_ids, hint, context, txt_ids, timesteps, y, guidance, control_type=kwargs.get("control_type", []))

comfy/lora.py

@@ -540,7 +540,7 @@ def calculate_weight(patches, weight, key, intermediate_dtype=torch.float32):
             b2 = comfy.model_management.cast_to_device(v[3].flatten(start_dim=1), weight.device, intermediate_dtype)
 
             try:
-                lora_diff = (torch.mm(b2, b1) + torch.mm(torch.mm(weight.flatten(start_dim=1), a2), a1)).reshape(weight.shape)
+                lora_diff = (torch.mm(b2, b1) + torch.mm(torch.mm(weight.flatten(start_dim=1).to(dtype=intermediate_dtype), a2), a1)).reshape(weight.shape)
                 if dora_scale is not None:
                     weight = function(weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype))
                 else:

notebooks/comfyui_colab.ipynb

@@ -79,7 +79,7 @@
         "#!wget -c https://huggingface.co/comfyanonymous/clip_vision_g/resolve/main/clip_vision_g.safetensors -P ./models/clip_vision/\n",
         "\n",
         "# SD1.5\n",
-        "!wget -c https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt -P ./models/checkpoints/\n",
+        "!wget -c https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/resolve/main/v1-5-pruned-emaonly-fp16.safetensors -P ./models/checkpoints/\n",
         "\n",
         "# SD2\n",
         "#!wget -c https://huggingface.co/stabilityai/stable-diffusion-2-1-base/resolve/main/v2-1_512-ema-pruned.safetensors -P ./models/checkpoints/\n",

script_examples/basic_api_example.py

@@ -43,7 +43,7 @@ prompt_text = """
     "4": {
         "class_type": "CheckpointLoaderSimple",
         "inputs": {
-            "ckpt_name": "v1-5-pruned-emaonly.ckpt"
+            "ckpt_name": "v1-5-pruned-emaonly.safetensors"
         }
     },
     "5": {

script_examples/websockets_api_example.py

@@ -84,7 +84,7 @@ prompt_text = """
     "4": {
         "class_type": "CheckpointLoaderSimple",
         "inputs": {
-            "ckpt_name": "v1-5-pruned-emaonly.ckpt"
+            "ckpt_name": "v1-5-pruned-emaonly.safetensors"
         }
     },
     "5": {

script_examples/websockets_api_example_ws_images.py

@@ -81,7 +81,7 @@ prompt_text = """
     "4": {
         "class_type": "CheckpointLoaderSimple",
         "inputs": {
-            "ckpt_name": "v1-5-pruned-emaonly.ckpt"
+            "ckpt_name": "v1-5-pruned-emaonly.safetensors"
         }
     },
     "5": {