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Mini-Patch

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TSC
2023-04-18 18:50:40 -05:00
committed by GitHub
parent 3ae297dcd8
commit de0641cd99
1 changed files with 12 additions and 13 deletions
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efficiency_nodes.py
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@@ -40,7 +40,7 @@ def pil2tensor(image: Image.Image) -> torch.Tensor:
# TSC Efficient Loader
# Track what objects have already been loaded into memory (*only for instances of this node)
# Track what objects have already been loaded into memory
loaded_objects = {
"ckpt": [], # (ckpt_name, location)
"clip": [], # (ckpt_name, location)
@@ -183,7 +183,7 @@ class TSC_KSampler:
"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
"preview_image": (["Disabled", "Enabled"],),
},
"optional": { "optional_vae": ("VAE",), #change to vae
"optional": { "optional_vae": ("VAE",),
"script": ("SCRIPT",),},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
}
@@ -301,7 +301,7 @@ class TSC_KSampler:
# Enable vae decode on next Hold
last_helds["vae_decode"][my_unique_id] = True
return {"ui": {"images": list()},
"result": (model, positive, negative, {"samples": latent}, vae, TSC_KSampler.empty_image,)}
"result": (model, positive, negative, {"samples": latent}, vae, last_images,)}
else:
# Decode images and store
images = vae.decode(latent).cpu()
@@ -326,7 +326,7 @@ class TSC_KSampler:
# If not in preview mode, return the results in the specified format
if preview_image == "Disabled":
return {"ui": {"images": list()},
"result": (model, positive, negative, last_latent, vae, TSC_KSampler.empty_image,)}
"result": (model, positive, negative, last_latent, vae, last_images,)}
# if preview_image == "Enabled":
else:
@@ -354,11 +354,6 @@ class TSC_KSampler:
"result": (model, positive, negative, {"samples": latent}, vae, images,)}
elif sampler_state == "Script":
# If not in preview mode, return the results in the specified format
if preview_image == "Disabled":
print('\033[31mKSampler(Efficient)[{}] Error:\033[0m Preview must be enabled to use Script mode.'.format(my_unique_id))
return {"ui": {"images": list()},
"result": (model, positive, negative, last_latent, vae, TSC_KSampler.empty_image,)}
# If no script input connected, set X_type and Y_type to "Nothing"
if script is None:
@@ -369,9 +364,9 @@ class TSC_KSampler:
X_type, X_value, Y_type, Y_value, grid_spacing, latent_id = script
if (X_type == "Nothing" and Y_type == "Nothing"):
print('\033[31mKSampler(Efficient)[{}] Error:\033[0m No valid script input detected'.format(my_unique_id))
print('\033[31mKSampler(Efficient)[{}] Error:\033[0m No valid script entry detected'.format(my_unique_id))
return {"ui": {"images": list()},
"result": (model, positive, negative, last_latent, vae, TSC_KSampler.empty_image,)}
"result": (model, positive, negative, last_latent, vae, last_images,)}
# Extract the 'samples' tensor from the dictionary
latent_image_tensor = latent_image['samples']
@@ -706,8 +701,12 @@ class TSC_KSampler:
results = preview_images(images, filename_prefix)
last_helds["results"][my_unique_id] = results
# Output image results to ui and node outputs
return {"ui": {"images": results}, "result": (model, positive, negative, {"samples": latent_new}, vae, images,)}
# If not in preview mode, return the results in the specified format
if preview_image == "Disabled":
return {"ui": {"images": list()}, "result": (model, positive, negative, last_latent, vae, images,)}
else:
# Output image results to ui and node outputs
return {"ui": {"images": results}, "result": (model, positive, negative, {"samples": latent_new}, vae, images,)}
# TSC XY Plot