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Merge branch 'comfyanonymous:master' into master

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patientx 2025-01-28 19:20:13 +03:00 committed by GitHub
commit a5c944f482
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2 changed files with 14 additions and 2 deletions
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11
comfy/utils.py
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@ -50,7 +50,16 @@ def load_torch_file(ckpt, safe_load=False, device=None):
if device is None: if device is None:
device = torch.device("cpu") device = torch.device("cpu")
if ckpt.lower().endswith(".safetensors") or ckpt.lower().endswith(".sft"): if ckpt.lower().endswith(".safetensors") or ckpt.lower().endswith(".sft"):
sd = safetensors.torch.load_file(ckpt, device=device.type) try:
sd = safetensors.torch.load_file(ckpt, device=device.type)
except Exception as e:
if len(e.args) > 0:
message = e.args[0]
if "HeaderTooLarge" in message:
raise ValueError("{}\n\nFile path: {}\n\nThe safetensors file is corrupt or invalid. Make sure this is actually a safetensors file and not a ckpt or pt or other filetype.".format(message, ckpt))
if "MetadataIncompleteBuffer" in message:
raise ValueError("{}\n\nFile path: {}\n\nThe safetensors file is incomplete. Check the file size and make sure you have copied/downloaded it correctly.".format(message, ckpt))
raise e
else: else:
if safe_load or ALWAYS_SAFE_LOAD: if safe_load or ALWAYS_SAFE_LOAD:
pl_sd = torch.load(ckpt, map_location=device, weights_only=True) pl_sd = torch.load(ckpt, map_location=device, weights_only=True)

5
latent_preview.py
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@ -12,7 +12,10 @@ MAX_PREVIEW_RESOLUTION = args.preview_size
def preview_to_image(latent_image): def preview_to_image(latent_image):
latents_ubyte = (((latent_image + 1.0) / 2.0).clamp(0, 1) # change scale from -1..1 to 0..1 latents_ubyte = (((latent_image + 1.0) / 2.0).clamp(0, 1) # change scale from -1..1 to 0..1
.mul(0xFF) # to 0..255 .mul(0xFF) # to 0..255
).to(device="cpu", dtype=torch.uint8, non_blocking=comfy.model_management.device_supports_non_blocking(latent_image.device)) )
if comfy.model_management.directml_enabled:
latents_ubyte = latents_ubyte.to(dtype=torch.uint8)
latents_ubyte = latents_ubyte.to(device="cpu", dtype=torch.uint8, non_blocking=comfy.model_management.device_supports_non_blocking(latent_image.device))
return Image.fromarray(latents_ubyte.numpy()) return Image.fromarray(latents_ubyte.numpy())