Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' into refactor/model-manager-2

Browse Source
This commit is contained in:
psychedelicious
2023-11-14 07:51:57 +11:00
committed by GitHub
parent 8c71ff37ae 7fcb8959fb
commit 4465f97cdf
253 changed files with 1712 additions and 3981 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
invokeai/backend/util/util.py
View File

@ -29,7 +29,7 @@ def log_txt_as_img(wh, xc, size=10):
# wh a tuple of (width, height)
# xc a list of captions to plot
b = len(xc)
txts = list()
txts = []
for bi in range(b):
txt = Image.new("RGB", wh, color="white")
draw = ImageDraw.Draw(txt)
@ -93,7 +93,7 @@ def instantiate_from_config(config, **kwargs):
elif config == "__is_unconditional__":
return None
raise KeyError("Expected key `target` to instantiate.")
return get_obj_from_str(config["target"])(**config.get("params", dict()), **kwargs)
return get_obj_from_str(config["target"])(**config.get("params", {}), **kwargs)
def get_obj_from_str(string, reload=False):
@ -231,11 +231,12 @@ def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10
angles = 2 * math.pi * rand_val
gradients = torch.stack((torch.cos(angles), torch.sin(angles)), dim=-1).to(device)
tile_grads = (
lambda slice1, slice2: gradients[slice1[0] : slice1[1], slice2[0] : slice2[1]]
.repeat_interleave(d[0], 0)
.repeat_interleave(d[1], 1)
)
def tile_grads(slice1, slice2):
return (
gradients[slice1[0] : slice1[1], slice2[0] : slice2[1]]
.repeat_interleave(d[0], 0)
.repeat_interleave(d[1], 1)
)
def dot(grad, shift):
return (