Delete nodes.py
Browse files
nodes.py
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# (c) City96 || Apache-2.0 (apache.org/licenses/LICENSE-2.0)
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import torch
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import gguf
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import copy
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import logging
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import comfy.sd
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import comfy.utils
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import comfy.model_management
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import comfy.model_patcher
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import folder_paths
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from .ops import GGMLTensor, GGMLOps, move_patch_to_device
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from .dequant import is_quantized, is_torch_compatible
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# Add a custom keys for files ending in .gguf
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if "unet_gguf" not in folder_paths.folder_names_and_paths:
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orig = folder_paths.folder_names_and_paths.get("diffusion_models", folder_paths.folder_names_and_paths.get("unet", [[], set()]))
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folder_paths.folder_names_and_paths["unet_gguf"] = (orig[0], {".gguf"})
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if "clip_gguf" not in folder_paths.folder_names_and_paths:
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orig = folder_paths.folder_names_and_paths.get("clip", [[], set()])
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folder_paths.folder_names_and_paths["clip_gguf"] = (orig[0], {".gguf"})
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def gguf_sd_loader_get_orig_shape(reader, tensor_name):
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field_key = f"comfy.gguf.orig_shape.{tensor_name}"
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field = reader.get_field(field_key)
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if field is None:
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return None
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# Has original shape metadata, so we try to decode it.
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if len(field.types) != 2 or field.types[0] != gguf.GGUFValueType.ARRAY or field.types[1] != gguf.GGUFValueType.INT32:
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raise TypeError(f"Bad original shape metadata for {field_key}: Expected ARRAY of INT32, got {field.types}")
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return torch.Size(tuple(int(field.parts[part_idx][0]) for part_idx in field.data))
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def gguf_sd_loader(path, handle_prefix="model.diffusion_model."):
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"""
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Read state dict as fake tensors
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"""
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reader = gguf.GGUFReader(path)
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# filter and strip prefix
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has_prefix = False
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if handle_prefix is not None:
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prefix_len = len(handle_prefix)
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tensor_names = set(tensor.name for tensor in reader.tensors)
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has_prefix = any(s.startswith(handle_prefix) for s in tensor_names)
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tensors = []
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for tensor in reader.tensors:
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sd_key = tensor_name = tensor.name
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if has_prefix:
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if not tensor_name.startswith(handle_prefix):
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continue
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sd_key = tensor_name[prefix_len:]
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tensors.append((sd_key, tensor))
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# detect and verify architecture
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compat = None
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arch_str = None
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arch_field = reader.get_field("general.architecture")
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if arch_field is not None:
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if len(arch_field.types) != 1 or arch_field.types[0] != gguf.GGUFValueType.STRING:
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raise TypeError(f"Bad type for GGUF general.architecture key: expected string, got {arch_field.types!r}")
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arch_str = str(arch_field.parts[arch_field.data[-1]], encoding="utf-8")
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if arch_str not in {"flux", "sd1", "sdxl", "t5", "t5encoder", "sd3"}:
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raise ValueError(f"Unexpected architecture type in GGUF file, expected one of flux, sd1, sdxl, t5encoder, sd3 but got {arch_str!r}")
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else: # stable-diffusion.cpp
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# import here to avoid changes to convert.py breaking regular models
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from .tools.convert import detect_arch
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arch_str = detect_arch(set(val[0] for val in tensors)).arch
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compat = "sd.cpp"
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# main loading loop
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state_dict = {}
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qtype_dict = {}
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for sd_key, tensor in tensors:
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tensor_name = tensor.name
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tensor_type_str = str(tensor.tensor_type)
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torch_tensor = torch.from_numpy(tensor.data) # mmap
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shape = gguf_sd_loader_get_orig_shape(reader, tensor_name)
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if shape is None:
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shape = torch.Size(tuple(int(v) for v in reversed(tensor.shape)))
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# Workaround for stable-diffusion.cpp SDXL detection.
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if compat == "sd.cpp" and arch_str == "sdxl":
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if any([tensor_name.endswith(x) for x in (".proj_in.weight", ".proj_out.weight")]):
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while len(shape) > 2 and shape[-1] == 1:
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shape = shape[:-1]
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# add to state dict
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if tensor.tensor_type in {gguf.GGMLQuantizationType.F32, gguf.GGMLQuantizationType.F16}:
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torch_tensor = torch_tensor.view(*shape)
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state_dict[sd_key] = GGMLTensor(torch_tensor, tensor_type=tensor.tensor_type, tensor_shape=shape)
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qtype_dict[tensor_type_str] = qtype_dict.get(tensor_type_str, 0) + 1
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# sanity check debug print
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print("\nggml_sd_loader:")
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for k,v in qtype_dict.items():
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print(f" {k:30}{v:3}")
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return state_dict
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# for remapping llama.cpp -> original key names
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clip_sd_map = {
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"enc.": "encoder.",
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".blk.": ".block.",
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"token_embd": "shared",
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"output_norm": "final_layer_norm",
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"attn_q": "layer.0.SelfAttention.q",
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"attn_k": "layer.0.SelfAttention.k",
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"attn_v": "layer.0.SelfAttention.v",
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"attn_o": "layer.0.SelfAttention.o",
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"attn_norm": "layer.0.layer_norm",
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"attn_rel_b": "layer.0.SelfAttention.relative_attention_bias",
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"ffn_up": "layer.1.DenseReluDense.wi_1",
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"ffn_down": "layer.1.DenseReluDense.wo",
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"ffn_gate": "layer.1.DenseReluDense.wi_0",
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"ffn_norm": "layer.1.layer_norm",
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}
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def gguf_clip_loader(path):
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raw_sd = gguf_sd_loader(path)
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assert "enc.blk.23.ffn_up.weight" in raw_sd, "Invalid Text Encoder!"
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sd = {}
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for k,v in raw_sd.items():
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for s,d in clip_sd_map.items():
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k = k.replace(s,d)
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sd[k] = v
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return sd
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# TODO: Temporary fix for now
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import collections
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class GGUFModelPatcher(comfy.model_patcher.ModelPatcher):
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patch_on_device = False
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def patch_weight_to_device(self, key, device_to=None, inplace_update=False):
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if key not in self.patches:
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return
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weight = comfy.utils.get_attr(self.model, key)
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try:
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from comfy.lora import calculate_weight
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except Exception:
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calculate_weight = self.calculate_weight
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patches = self.patches[key]
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if is_quantized(weight):
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out_weight = weight.to(device_to)
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patches = move_patch_to_device(patches, self.load_device if self.patch_on_device else self.offload_device)
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# TODO: do we ever have legitimate duplicate patches? (i.e. patch on top of patched weight)
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out_weight.patches = [(calculate_weight, patches, key)]
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else:
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inplace_update = self.weight_inplace_update or inplace_update
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if key not in self.backup:
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self.backup[key] = collections.namedtuple('Dimension', ['weight', 'inplace_update'])(
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weight.to(device=self.offload_device, copy=inplace_update), inplace_update
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)
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if device_to is not None:
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temp_weight = comfy.model_management.cast_to_device(weight, device_to, torch.float32, copy=True)
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else:
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temp_weight = weight.to(torch.float32, copy=True)
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out_weight = calculate_weight(patches, temp_weight, key)
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out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype)
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if inplace_update:
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comfy.utils.copy_to_param(self.model, key, out_weight)
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else:
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comfy.utils.set_attr_param(self.model, key, out_weight)
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def unpatch_model(self, device_to=None, unpatch_weights=True):
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if unpatch_weights:
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for p in self.model.parameters():
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if is_torch_compatible(p):
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continue
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patches = getattr(p, "patches", [])
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if len(patches) > 0:
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p.patches = []
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# TODO: Find another way to not unload after patches
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return super().unpatch_model(device_to=device_to, unpatch_weights=unpatch_weights)
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mmap_released = False
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def load(self, *args, force_patch_weights=False, **kwargs):
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# always call `patch_weight_to_device` even for lowvram
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super().load(*args, force_patch_weights=True, **kwargs)
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# make sure nothing stays linked to mmap after first load
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if not self.mmap_released:
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linked = []
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if kwargs.get("lowvram_model_memory", 0) > 0:
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for n, m in self.model.named_modules():
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if hasattr(m, "weight"):
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device = getattr(m.weight, "device", None)
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if device == self.offload_device:
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linked.append((n, m))
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continue
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if hasattr(m, "bias"):
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device = getattr(m.bias, "device", None)
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if device == self.offload_device:
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linked.append((n, m))
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continue
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if linked:
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print(f"Attempting to release mmap ({len(linked)})")
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for n, m in linked:
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# TODO: possible to OOM, find better way to detach
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m.to(self.load_device).to(self.offload_device)
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self.mmap_released = True
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def clone(self, *args, **kwargs):
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n = GGUFModelPatcher(self.model, self.load_device, self.offload_device, self.size, weight_inplace_update=self.weight_inplace_update)
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n.patches = {}
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for k in self.patches:
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n.patches[k] = self.patches[k][:]
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n.patches_uuid = self.patches_uuid
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n.object_patches = self.object_patches.copy()
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n.model_options = copy.deepcopy(self.model_options)
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n.backup = self.backup
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n.object_patches_backup = self.object_patches_backup
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n.patch_on_device = getattr(self, "patch_on_device", False)
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return n
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class UnetLoaderGGUF:
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@classmethod
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def INPUT_TYPES(s):
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unet_names = [x for x in folder_paths.get_filename_list("unet_gguf")]
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return {
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"required": {
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"unet_name": (unet_names,),
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}
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}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "load_unet"
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CATEGORY = "bootleg"
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TITLE = "Unet Loader (GGUF)"
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def load_unet(self, unet_name, dequant_dtype=None, patch_dtype=None, patch_on_device=None):
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ops = GGMLOps()
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if dequant_dtype in ("default", None):
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ops.Linear.dequant_dtype = None
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elif dequant_dtype in ["target"]:
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ops.Linear.dequant_dtype = dequant_dtype
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else:
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ops.Linear.dequant_dtype = getattr(torch, dequant_dtype)
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if patch_dtype in ("default", None):
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ops.Linear.patch_dtype = None
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elif patch_dtype in ["target"]:
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ops.Linear.patch_dtype = patch_dtype
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else:
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ops.Linear.patch_dtype = getattr(torch, patch_dtype)
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# init model
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unet_path = folder_paths.get_full_path("unet", unet_name)
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sd = gguf_sd_loader(unet_path)
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model = comfy.sd.load_diffusion_model_state_dict(
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sd, model_options={"custom_operations": ops}
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)
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if model is None:
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logging.error("ERROR UNSUPPORTED UNET {}".format(unet_path))
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raise RuntimeError("ERROR: Could not detect model type of: {}".format(unet_path))
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model = GGUFModelPatcher.clone(model)
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model.patch_on_device = patch_on_device
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return (model,)
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class UnetLoaderGGUFAdvanced(UnetLoaderGGUF):
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@classmethod
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def INPUT_TYPES(s):
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unet_names = [x for x in folder_paths.get_filename_list("unet_gguf")]
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return {
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"required": {
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"unet_name": (unet_names,),
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"dequant_dtype": (["default", "target", "float32", "float16", "bfloat16"], {"default": "default"}),
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"patch_dtype": (["default", "target", "float32", "float16", "bfloat16"], {"default": "default"}),
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"patch_on_device": ("BOOLEAN", {"default": False}),
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}
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}
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TITLE = "Unet Loader (GGUF/Advanced)"
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clip_name_dict = {
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"stable_diffusion": comfy.sd.CLIPType.STABLE_DIFFUSION,
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"stable_cascade": comfy.sd.CLIPType.STABLE_CASCADE,
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"stable_audio": comfy.sd.CLIPType.STABLE_AUDIO,
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"sdxl": comfy.sd.CLIPType.STABLE_DIFFUSION,
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"sd3": comfy.sd.CLIPType.SD3,
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"flux": comfy.sd.CLIPType.FLUX,
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}
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class CLIPLoaderGGUF:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"clip_name": (s.get_filename_list(),),
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"type": (["stable_diffusion", "stable_cascade", "sd3", "stable_audio"],),
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}
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}
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RETURN_TYPES = ("CLIP",)
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FUNCTION = "load_clip"
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CATEGORY = "bootleg"
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TITLE = "CLIPLoader (GGUF)"
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@classmethod
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def get_filename_list(s):
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files = []
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files += folder_paths.get_filename_list("clip")
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files += folder_paths.get_filename_list("clip_gguf")
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return sorted(files)
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def load_data(self, ckpt_paths):
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clip_data = []
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for p in ckpt_paths:
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if p.endswith(".gguf"):
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clip_data.append(gguf_clip_loader(p))
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else:
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sd = comfy.utils.load_torch_file(p, safe_load=True)
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clip_data.append(
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{k:GGMLTensor(v, tensor_type=gguf.GGMLQuantizationType.F16, tensor_shape=v.shape) for k,v in sd.items()}
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)
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return clip_data
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def load_patcher(self, clip_paths, clip_type, clip_data):
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clip = comfy.sd.load_text_encoder_state_dicts(
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clip_type = clip_type,
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state_dicts = clip_data,
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model_options = {
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"custom_operations": GGMLOps,
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"initial_device": comfy.model_management.text_encoder_offload_device()
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},
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embedding_directory = folder_paths.get_folder_paths("embeddings"),
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)
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clip.patcher = GGUFModelPatcher.clone(clip.patcher)
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# for some reason this is just missing in some SAI checkpoints
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if getattr(clip.cond_stage_model, "clip_l", None) is not None:
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if getattr(clip.cond_stage_model.clip_l.transformer.text_projection.weight, "tensor_shape", None) is None:
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clip.cond_stage_model.clip_l.transformer.text_projection = comfy.ops.manual_cast.Linear(768, 768)
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if getattr(clip.cond_stage_model, "clip_g", None) is not None:
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if getattr(clip.cond_stage_model.clip_g.transformer.text_projection.weight, "tensor_shape", None) is None:
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clip.cond_stage_model.clip_g.transformer.text_projection = comfy.ops.manual_cast.Linear(1280, 1280)
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return clip
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def load_clip(self, clip_name, type="stable_diffusion"):
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clip_path = folder_paths.get_full_path("clip", clip_name)
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clip_type = clip_name_dict.get(type, comfy.sd.CLIPType.STABLE_DIFFUSION)
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351 |
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return (self.load_patcher([clip_path], clip_type, self.load_data([clip_path])),)
|
352 |
-
|
353 |
-
class DualCLIPLoaderGGUF(CLIPLoaderGGUF):
|
354 |
-
@classmethod
|
355 |
-
def INPUT_TYPES(s):
|
356 |
-
file_options = (s.get_filename_list(), )
|
357 |
-
return {
|
358 |
-
"required": {
|
359 |
-
"clip_name1": file_options,
|
360 |
-
"clip_name2": file_options,
|
361 |
-
"type": (("sdxl", "sd3", "flux"), ),
|
362 |
-
}
|
363 |
-
}
|
364 |
-
|
365 |
-
TITLE = "DualCLIPLoader (GGUF)"
|
366 |
-
|
367 |
-
def load_clip(self, clip_name1, clip_name2, type):
|
368 |
-
clip_path1 = folder_paths.get_full_path("clip", clip_name1)
|
369 |
-
clip_path2 = folder_paths.get_full_path("clip", clip_name2)
|
370 |
-
clip_paths = (clip_path1, clip_path2)
|
371 |
-
clip_type = clip_name_dict.get(type, comfy.sd.CLIPType.STABLE_DIFFUSION)
|
372 |
-
return (self.load_patcher(clip_paths, clip_type, self.load_data(clip_paths)),)
|
373 |
-
|
374 |
-
class TripleCLIPLoaderGGUF(CLIPLoaderGGUF):
|
375 |
-
@classmethod
|
376 |
-
def INPUT_TYPES(s):
|
377 |
-
file_options = (s.get_filename_list(), )
|
378 |
-
return {
|
379 |
-
"required": {
|
380 |
-
"clip_name1": file_options,
|
381 |
-
"clip_name2": file_options,
|
382 |
-
"clip_name3": file_options,
|
383 |
-
}
|
384 |
-
}
|
385 |
-
|
386 |
-
TITLE = "TripleCLIPLoader (GGUF)"
|
387 |
-
|
388 |
-
def load_clip(self, clip_name1, clip_name2, clip_name3, type="sd3"):
|
389 |
-
clip_path1 = folder_paths.get_full_path("clip", clip_name1)
|
390 |
-
clip_path2 = folder_paths.get_full_path("clip", clip_name2)
|
391 |
-
clip_path3 = folder_paths.get_full_path("clip", clip_name3)
|
392 |
-
clip_paths = (clip_path1, clip_path2, clip_path3)
|
393 |
-
clip_type = clip_name_dict.get(type, comfy.sd.CLIPType.STABLE_DIFFUSION)
|
394 |
-
return (self.load_patcher(clip_paths, clip_type, self.load_data(clip_paths)),)
|
395 |
-
|
396 |
-
class UnetLoaderSD3GGUF(UnetLoaderGGUF):
|
397 |
-
@classmethod
|
398 |
-
def INPUT_TYPES(s):
|
399 |
-
unet_names = [x for x in folder_paths.get_filename_list("unet_gguf")]
|
400 |
-
return {
|
401 |
-
"required": {
|
402 |
-
"unet_name": (unet_names,),
|
403 |
-
}
|
404 |
-
}
|
405 |
-
|
406 |
-
RETURN_TYPES = ("MODEL",)
|
407 |
-
FUNCTION = "load_unet"
|
408 |
-
CATEGORY = "bootleg"
|
409 |
-
TITLE = "Unet Loader SD3 (GGUF)"
|
410 |
-
|
411 |
-
def load_unet(self, unet_name, dequant_dtype=None, patch_dtype=None, patch_on_device=None):
|
412 |
-
ops = GGMLOps()
|
413 |
-
|
414 |
-
if dequant_dtype in ("default", None):
|
415 |
-
ops.Linear.dequant_dtype = None
|
416 |
-
elif dequant_dtype in ["target"]:
|
417 |
-
ops.Linear.dequant_dtype = dequant_dtype
|
418 |
-
else:
|
419 |
-
ops.Linear.dequant_dtype = getattr(torch, dequant_dtype)
|
420 |
-
|
421 |
-
if patch_dtype in ("default", None):
|
422 |
-
ops.Linear.patch_dtype = None
|
423 |
-
elif patch_dtype in ["target"]:
|
424 |
-
ops.Linear.patch_dtype = patch_dtype
|
425 |
-
else:
|
426 |
-
ops.Linear.patch_dtype = getattr(torch, patch_dtype)
|
427 |
-
|
428 |
-
# init model
|
429 |
-
unet_path = folder_paths.get_full_path("unet", unet_name)
|
430 |
-
sd = gguf_sd_loader(unet_path)
|
431 |
-
model = comfy.sd.load_diffusion_model_state_dict(
|
432 |
-
sd, model_options={"custom_operations": ops, "model_type": "sd3"}
|
433 |
-
)
|
434 |
-
if model is None:
|
435 |
-
logging.error("ERROR UNSUPPORTED UNET {}".format(unet_path))
|
436 |
-
raise RuntimeError("ERROR: Could not detect model type of: {}".format(unet_path))
|
437 |
-
model = GGUFModelPatcher.clone(model)
|
438 |
-
model.patch_on_device = patch_on_device
|
439 |
-
return (model,)
|
440 |
-
|
441 |
-
class UnetLoaderSD3GGUFAdvanced(UnetLoaderSD3GGUF):
|
442 |
-
@classmethod
|
443 |
-
def INPUT_TYPES(s):
|
444 |
-
unet_names = [x for x in folder_paths.get_filename_list("unet_gguf")]
|
445 |
-
return {
|
446 |
-
"required": {
|
447 |
-
"unet_name": (unet_names,),
|
448 |
-
"dequant_dtype": (["default", "target", "float32", "float16", "bfloat16"], {"default": "default"}),
|
449 |
-
"patch_dtype": (["default", "target", "float32", "float16", "bfloat16"], {"default": "default"}),
|
450 |
-
"patch_on_device": ("BOOLEAN", {"default": False}),
|
451 |
-
}
|
452 |
-
}
|
453 |
-
TITLE = "Unet Loader SD3 (GGUF/Advanced)"
|
454 |
-
|
455 |
-
|
456 |
-
|
457 |
-
NODE_CLASS_MAPPINGS = {
|
458 |
-
"UnetLoaderGGUF": UnetLoaderGGUF,
|
459 |
-
"CLIPLoaderGGUF": CLIPLoaderGGUF,
|
460 |
-
"DualCLIPLoaderGGUF": DualCLIPLoaderGGUF,
|
461 |
-
"TripleCLIPLoaderGGUF": TripleCLIPLoaderGGUF,
|
462 |
-
"UnetLoaderGGUFAdvanced": UnetLoaderGGUFAdvanced,
|
463 |
-
"UnetLoaderSD3GGUF": UnetLoaderSD3GGUF,
|
464 |
-
"UnetLoaderSD3GGUFAdvanced": UnetLoaderSD3GGUFAdvanced,
|
465 |
-
}
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