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Merge branch 'master' of github.com:comfyanonymous/ComfyUI

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This commit is contained in:
doctorpangloss 2024-08-02 10:55:02 -07:00
commit c348b37b7c
7 changed files with 45 additions and 12 deletions
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14
comfy/ldm/flux/model.py
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@ -124,10 +124,16 @@ class Flux(nn.Module):
def forward(self, x, timestep, context, y, guidance, **kwargs):
bs, c, h, w = x.shape
img = rearrange(x, "b c (h ph) (w pw) -> b (h w) (c ph pw)", ph=2, pw=2)
patch_size = 2
pad_h = (patch_size - h % 2) % patch_size
pad_w = (patch_size - w % 2) % patch_size
h_len = (h // 2)
w_len = (w // 2)
x = torch.nn.functional.pad(x, (0, pad_w, 0, pad_h), mode='circular')
img = rearrange(x, "b c (h ph) (w pw) -> b (h w) (c ph pw)", ph=patch_size, pw=patch_size)
h_len = ((h + (patch_size // 2)) // patch_size)
w_len = ((w + (patch_size // 2)) // patch_size)
img_ids = torch.zeros((h_len, w_len, 3), device=x.device, dtype=x.dtype)
img_ids[..., 1] = img_ids[..., 1] + torch.linspace(0, h_len - 1, steps=h_len, device=x.device, dtype=x.dtype)[:, None]
img_ids[..., 2] = img_ids[..., 2] + torch.linspace(0, w_len - 1, steps=w_len, device=x.device, dtype=x.dtype)[None, :]
@ -135,4 +141,4 @@ class Flux(nn.Module):
txt_ids = torch.zeros((bs, context.shape[1], 3), device=x.device, dtype=x.dtype)
out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance)
return rearrange(out, "b (h w) (c ph pw) -> b c (h ph) (w pw)", h=h_len, w=w_len, ph=2, pw=2)
return rearrange(out, "b (h w) (c ph pw) -> b c (h ph) (w pw)", h=h_len, w=w_len, ph=2, pw=2)[:,:,:h,:w]

9
comfy/nodes/base_nodes.py
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@ -823,9 +823,14 @@ class UNETLoader:
CATEGORY = "advanced/loaders"
def load_unet(self, unet_name, weight_dtype):
weight_dtype = {"default":None, "fp8_e4m3fn":torch.float8_e4m3fn, "fp8_e5m2":torch.float8_e4m3fn}[weight_dtype]
dtype = None
if weight_dtype == "fp8_e4m3fn":
dtype = torch.float8_e4m3fn
elif weight_dtype == "fp8_e5m2":
dtype = torch.float8_e5m2
unet_path = get_or_download("unet", unet_name, KNOWN_UNET_MODELS)
model = sd.load_unet(unet_path, dtype=weight_dtype)
model = sd.load_unet(unet_path, dtype=dtype)
return (model,)
class CLIPLoader:

5
comfy/web/scripts/pnginfo.js
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@ -190,9 +190,10 @@ function parseVorbisComment(dataView) {
const comment = getString(dataView, offset, commentLength);
offset += commentLength;
const [key, value] = comment.split('=');
const ind = comment.indexOf('=')
const key = comment.substring(0, ind);
comments[key] = value;
comments[key] = comment.substring(ind+1);
}
return comments;

1
comfy_extras/nodes/nodes_audio.py
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@ -8,6 +8,7 @@ import io
import json
import struct
import random
import hashlib
from comfy.cli_args import args
class EmptyLatentAudio:

22
comfy_extras/nodes/nodes_flux.py
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@ -1,3 +1,4 @@
import node_helpers
class CLIPTextEncodeFlux:
@classmethod
@ -11,7 +12,7 @@ class CLIPTextEncodeFlux:
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
CATEGORY = "advanced/conditioning"
CATEGORY = "advanced/conditioning/flux"
def encode(self, clip, clip_l, t5xxl, guidance):
tokens = clip.tokenize(clip_l)
@ -22,6 +23,25 @@ class CLIPTextEncodeFlux:
output["guidance"] = guidance
return ([[cond, output]], )
class FluxGuidance:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"conditioning": ("CONDITIONING", ),
"guidance": ("FLOAT", {"default": 3.5, "min": 0.0, "max": 100.0, "step": 0.1}),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "append"
CATEGORY = "advanced/conditioning/flux"
def append(self, conditioning, guidance):
c = node_helpers.conditioning_set_values(conditioning, {"guidance": guidance})
return (c, )
NODE_CLASS_MAPPINGS = {
"CLIPTextEncodeFlux": CLIPTextEncodeFlux,
"FluxGuidance": FluxGuidance,
}

2
comfy_extras/nodes/nodes_pag.py
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@ -12,7 +12,7 @@ class PerturbedAttentionGuidance:
return {
"required": {
"model": ("MODEL",),
"scale": ("FLOAT", {"default": 3.0, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01}),
"scale": ("FLOAT", {"default": 3.0, "min": 0.0, "max": 100.0, "step": 0.01, "round": 0.01}),
}
}

4
comfy_extras/nodes/nodes_sag.py
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@ -96,8 +96,8 @@ class SelfAttentionGuidance:
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"scale": ("FLOAT", {"default": 0.5, "min": -2.0, "max": 5.0, "step": 0.01, "round": 0.01}),
"blur_sigma": ("FLOAT", {"default": 2.0, "min": 0.0, "max": 10.0, "step": 0.01, "round": 0.01}),
"scale": ("FLOAT", {"default": 0.5, "min": -2.0, "max": 5.0, "step": 0.01}),
"blur_sigma": ("FLOAT", {"default": 2.0, "min": 0.0, "max": 10.0, "step": 0.1}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"