The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 

27 lines
1.3 KiB

from comfy import sd1_clip
import torch
import os
class SD2ClipModel(sd1_clip.SD1ClipModel):
def __init__(self, arch="ViT-H-14", device="cpu", max_length=77, freeze=True, layer="penultimate", layer_idx=None, textmodel_path=None, dtype=None):
if layer == "penultimate":
layer="hidden"
layer_idx=23
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sd2_clip_config.json")
super().__init__(device=device, freeze=freeze, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, textmodel_path=textmodel_path, dtype=dtype)
self.empty_tokens = [[49406] + [49407] + [0] * 75]
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, embedding_directory=None):
super().__init__(tokenizer_path, pad_with_end=False, embedding_directory=embedding_directory, embedding_size=1024)