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Merge branch 'comfyanonymous:master' into master

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efwfe 2024-07-23 09:36:49 +08:00 committed by GitHub
commit 5a1ef5aa0b
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5 changed files with 30 additions and 17 deletions
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13
comfy/cldm/cldm.py
View File

@ -13,6 +13,7 @@ from ..ldm.modules.diffusionmodules.util import (
from ..ldm.modules.attention import SpatialTransformer
from ..ldm.modules.diffusionmodules.openaimodel import UNetModel, TimestepEmbedSequential, ResBlock, Downsample
from ..ldm.util import exists
from .control_types import UNION_CONTROLNET_TYPES
from collections import OrderedDict
import comfy.ops
from comfy.ldm.modules.attention import optimized_attention
@ -390,6 +391,18 @@ class ControlNet(nn.Module):
if self.control_add_embedding is not None: #Union Controlnet
control_type = kwargs.get("control_type", [])
if any([c >= self.num_control_type for c in control_type]):
max_type = max(control_type)
max_type_name = {
v: k for k, v in UNION_CONTROLNET_TYPES.items()
}[max_type]
raise ValueError(
f"Control type {max_type_name}({max_type}) is out of range for the number of control types" +
f"({self.num_control_type}) supported.\n" +
"Please consider using the ProMax ControlNet Union model.\n" +
"https://huggingface.co/xinsir/controlnet-union-sdxl-1.0/tree/main"
)
emb += self.control_add_embedding(control_type, emb.dtype, emb.device)
if len(control_type) > 0:
if len(hint.shape) < 5:

10
comfy/cldm/control_types.py Normal file
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@ -0,0 +1,10 @@
UNION_CONTROLNET_TYPES = {
"openpose": 0,
"depth": 1,
"hed/pidi/scribble/ted": 2,
"canny/lineart/anime_lineart/mlsd": 3,
"normal": 4,
"segment": 5,
"tile": 6,
"repaint": 7,
}

4
comfy/text_encoders/aura_t5.py
View File

@ -1,5 +1,5 @@
from comfy import sd1_clip
from .llama_tokenizer import LLAMATokenizer
from .spiece_tokenizer import SPieceTokenizer
import comfy.text_encoders.t5
import os
@ -11,7 +11,7 @@ class PT5XlModel(sd1_clip.SDClipModel):
class PT5XlTokenizer(sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None):
tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer"), "tokenizer.model")
super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LLAMATokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1)
super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=SPieceTokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1)
class AuraT5Tokenizer(sd1_clip.SD1Tokenizer):
def __init__(self, embedding_directory=None):

4
comfy/text_encoders/llama_tokenizer.py → comfy/text_encoders/spiece_tokenizer.py
View File

@ -1,9 +1,9 @@
import os
class LLAMATokenizer:
class SPieceTokenizer:
@staticmethod
def from_pretrained(path):
return LLAMATokenizer(path)
return SPieceTokenizer(path)
def __init__(self, tokenizer_path):
import sentencepiece

16
comfy_extras/nodes_controlnet.py
View File

@ -1,20 +1,10 @@
UNION_CONTROLNET_TYPES = {"auto": -1,
"openpose": 0,
"depth": 1,
"hed/pidi/scribble/ted": 2,
"canny/lineart/anime_lineart/mlsd": 3,
"normal": 4,
"segment": 5,
"tile": 6,
"repaint": 7,
}
from comfy.cldm.control_types import UNION_CONTROLNET_TYPES
class SetUnionControlNetType:
@classmethod
def INPUT_TYPES(s):
return {"required": {"control_net": ("CONTROL_NET", ),
"type": (list(UNION_CONTROLNET_TYPES.keys()),)
"type": (["auto"] + list(UNION_CONTROLNET_TYPES.keys()),)
}}
CATEGORY = "conditioning/controlnet"
@ -24,7 +14,7 @@ class SetUnionControlNetType:
def set_controlnet_type(self, control_net, type):
control_net = control_net.copy()
type_number = UNION_CONTROLNET_TYPES[type]
type_number = UNION_CONTROLNET_TYPES.get(type, -1)
if type_number >= 0:
control_net.set_extra_arg("control_type", [type_number])
else: