Merge remote-tracking branch 'origin/master' into group-nodes

This commit is contained in:
pythongosssss 2023-11-19 20:29:47 +00:00
commit 823cac376b
5 changed files with 38 additions and 8 deletions

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@ -77,9 +77,9 @@ class ModelSamplingDiscrete(torch.nn.Module):
def percent_to_sigma(self, percent):
if percent <= 0.0:
return torch.tensor(999999999.9)
return 999999999.9
if percent >= 1.0:
return torch.tensor(0.0)
return 0.0
percent = 1.0 - percent
return self.sigma(torch.tensor(percent * 999.0))
return self.sigma(torch.tensor(percent * 999.0)).item()

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@ -0,0 +1,29 @@
import nodes
MAX_RESOLUTION = nodes.MAX_RESOLUTION
class ImageCrop:
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
"width": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}),
"height": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}),
"x": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
"y": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "crop"
CATEGORY = "image/transform"
def crop(self, image, width, height, x, y):
x = min(x, image.shape[2] - 1)
y = min(y, image.shape[1] - 1)
to_x = width + x
to_y = height + y
img = image[:,y:to_y, x:to_x, :]
return (img,)
NODE_CLASS_MAPPINGS = {
"ImageCrop": ImageCrop,
}

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@ -67,11 +67,11 @@ class ModelSamplingDiscreteLCM(torch.nn.Module):
def percent_to_sigma(self, percent):
if percent <= 0.0:
return torch.tensor(999999999.9)
return 999999999.9
if percent >= 1.0:
return torch.tensor(0.0)
return 0.0
percent = 1.0 - percent
return self.sigma(torch.tensor(percent * 999.0))
return self.sigma(torch.tensor(percent * 999.0)).item()
def rescale_zero_terminal_snr_sigmas(sigmas):

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@ -16,8 +16,8 @@ class PatchModelAddDownscale:
CATEGORY = "_for_testing"
def patch(self, model, block_number, downscale_factor, start_percent, end_percent, downscale_after_skip):
sigma_start = model.model.model_sampling.percent_to_sigma(start_percent).item()
sigma_end = model.model.model_sampling.percent_to_sigma(end_percent).item()
sigma_start = model.model.model_sampling.percent_to_sigma(start_percent)
sigma_end = model.model.model_sampling.percent_to_sigma(end_percent)
def input_block_patch(h, transformer_options):
if transformer_options["block"][1] == block_number:

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@ -1800,6 +1800,7 @@ def init_custom_nodes():
"nodes_hypertile.py",
"nodes_model_advanced.py",
"nodes_model_downscale.py",
"nodes_images.py",
]
for node_file in extras_files: