Add a CLIPLoader node to load standalone clip weights.

Put them in models/clip
This commit is contained in:
comfyanonymous 2023-02-05 15:20:18 -05:00
parent 56d802e1f3
commit 1de5aa6a59
4 changed files with 53 additions and 6 deletions

View File

@ -274,9 +274,15 @@ class CLIP:
n.tokenizer = self.tokenizer
return n
def load_from_state_dict(self, sd):
self.cond_stage_model.transformer.load_state_dict(sd, strict=False)
def add_patches(self, patches, strength=1.0):
return self.patcher.add_patches(patches, strength)
def clip_layer(self, layer_idx):
return self.cond_stage_model.clip_layer(layer_idx)
def encode(self, text):
tokens = self.tokenizer.tokenize_with_weights(text)
try:
@ -317,6 +323,16 @@ class VAE:
samples = samples.cpu()
return samples
def load_clip(ckpt_path, embedding_directory=None):
clip_data = load_torch_file(ckpt_path)
config = {}
if "text_model.encoder.layers.22.mlp.fc1.weight" in clip_data:
config['target'] = 'ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder'
else:
config['target'] = 'ldm.modules.encoders.modules.FrozenCLIPEmbedder'
clip = CLIP(config=config, embedding_directory=embedding_directory)
clip.load_from_state_dict(clip_data)
return clip
def load_checkpoint(config_path, ckpt_path, output_vae=True, output_clip=True, embedding_directory=None):
config = OmegaConf.load(config_path)

View File

@ -8,15 +8,26 @@ class SD2ClipModel(sd1_clip.SD1ClipModel):
super().__init__(device=device, freeze=freeze, textmodel_json_config=textmodel_json_config)
self.empty_tokens = [[49406] + [49407] + [0] * 75]
if layer == "last":
layer_idx = -1
pass
elif layer == "penultimate":
layer_idx = -2
layer_idx = -1
self.clip_layer(layer_idx)
elif self.layer == "hidden":
assert layer_idx is not None
assert abs(layer_idx) < 24
self.clip_layer(layer_idx)
else:
raise NotImplementedError()
self.clip_layer(layer_idx)
def clip_layer(self, layer_idx):
if layer_idx < 0:
layer_idx -= 1 #The real last layer of SD2.x clip is the penultimate one. The last one might contain garbage.
if abs(layer_idx) >= 24:
self.layer = "hidden"
self.layer_idx = -2
else:
self.layer = "hidden"
self.layer_idx = layer_idx
class SD2Tokenizer(sd1_clip.SD1Tokenizer):
def __init__(self, tokenizer_path=None):

View File

@ -17,7 +17,7 @@ import comfy.samplers
import comfy.sd
supported_ckpt_extensions = ['.ckpt']
supported_pt_extensions = ['.ckpt', '.pt']
supported_pt_extensions = ['.ckpt', '.pt', '.bin']
try:
import safetensors.torch
supported_ckpt_extensions += ['.safetensors']
@ -114,6 +114,7 @@ class CheckpointLoader:
models_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "models")
config_dir = os.path.join(models_dir, "configs")
ckpt_dir = os.path.join(models_dir, "checkpoints")
embedding_directory = os.path.join(models_dir, "embeddings")
@classmethod
def INPUT_TYPES(s):
@ -127,8 +128,7 @@ class CheckpointLoader:
def load_checkpoint(self, config_name, ckpt_name, output_vae=True, output_clip=True):
config_path = os.path.join(self.config_dir, config_name)
ckpt_path = os.path.join(self.ckpt_dir, ckpt_name)
embedding_directory = os.path.join(self.models_dir, "embeddings")
return comfy.sd.load_checkpoint(config_path, ckpt_path, output_vae=True, output_clip=True, embedding_directory=embedding_directory)
return comfy.sd.load_checkpoint(config_path, ckpt_path, output_vae=True, output_clip=True, embedding_directory=self.embedding_directory)
class LoraLoader:
models_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "models")
@ -168,6 +168,25 @@ class VAELoader:
vae = comfy.sd.VAE(ckpt_path=vae_path)
return (vae,)
class CLIPLoader:
models_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "models")
clip_dir = os.path.join(models_dir, "clip")
@classmethod
def INPUT_TYPES(s):
return {"required": { "clip_name": (filter_files_extensions(os.listdir(s.clip_dir), supported_pt_extensions), ),
"stop_at_clip_layer": ("INT", {"default": -1, "min": -24, "max": -1, "step": 1}),
}}
RETURN_TYPES = ("CLIP",)
FUNCTION = "load_clip"
CATEGORY = "loaders"
def load_clip(self, clip_name, stop_at_clip_layer):
clip_path = os.path.join(self.clip_dir, clip_name)
clip = comfy.sd.load_clip(ckpt_path=clip_path, embedding_directory=CheckpointLoader.embedding_directory)
clip.clip_layer(stop_at_clip_layer)
return (clip,)
class EmptyLatentImage:
def __init__(self, device="cpu"):
self.device = device
@ -549,6 +568,7 @@ NODE_CLASS_MAPPINGS = {
"LatentFlip": LatentFlip,
"LatentCrop": LatentCrop,
"LoraLoader": LoraLoader,
"CLIPLoader": CLIPLoader,
}