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ffacb580d1 |
2
.github/workflows/stable-release.yml
vendored
2
.github/workflows/stable-release.yml
vendored
@ -145,6 +145,8 @@ jobs:
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cp -r ComfyUI/.ci/windows_${{ inputs.rel_name }}_base_files/* ./
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cp ../update_comfyui_and_python_dependencies.bat ./update/
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echo 'local-portable' > ComfyUI/.comfy_environment
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cd ..
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"C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=9 -mfb=128 -md=768m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
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@ -1460,7 +1460,7 @@ def pytorch_attention_enabled():
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return ENABLE_PYTORCH_ATTENTION
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def pytorch_attention_enabled_vae():
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if is_amd():
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if is_amd() and not SUPPORT_FP8_OPS: # exclude RDNA4 (gfx1200, gfx1201) and CDNA4 (gfx950) that support fp8
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return False # enabling pytorch attention on AMD currently causes crash when doing high res
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return pytorch_attention_enabled()
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@ -26,6 +26,7 @@ import uuid
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from typing import Callable, Optional
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import torch
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import tqdm
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import comfy.float
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import comfy.hooks
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@ -1651,7 +1652,11 @@ class ModelPatcherDynamic(ModelPatcher):
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self.model.model_loaded_weight_memory += casted_buf.numel() * casted_buf.element_size()
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force_load_stat = f" Force pre-loaded {len(self.backup)} weights: {self.model.model_loaded_weight_memory // 1024} KB." if len(self.backup) > 0 else ""
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logging.info(f"Model {self.model.__class__.__name__} prepared for dynamic VRAM loading. {allocated_size // (1024 ** 2)}MB Staged. {num_patches} patches attached.{force_load_stat}")
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log_key = (self.patches_uuid, allocated_size, num_patches, len(self.backup), self.model.model_loaded_weight_memory)
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in_loop = bool(getattr(tqdm.tqdm, "_instances", None))
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level = logging.DEBUG if in_loop and getattr(self, "_last_prepare_log_key", None) == log_key else logging.INFO
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self._last_prepare_log_key = log_key
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logging.log(level, f"Model {self.model.__class__.__name__} prepared for dynamic VRAM loading. {allocated_size // (1024 ** 2)}MB Staged. {num_patches} patches attached.{force_load_stat}")
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self.model.device = device_to
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self.model.current_weight_patches_uuid = self.patches_uuid
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@ -444,7 +444,7 @@ class VAE:
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if 'decoder.up_blocks.0.resnets.0.norm1.weight' in sd.keys(): #diffusers format
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sd = diffusers_convert.convert_vae_state_dict(sd)
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if model_management.is_amd():
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if model_management.is_amd() and not model_management.SUPPORT_FP8_OPS: # exclude RDNA4 (gfx1200, gfx1201) and CDNA4 (gfx950) that support fp8
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VAE_KL_MEM_RATIO = 2.73
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else:
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VAE_KL_MEM_RATIO = 1.0
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@ -560,7 +560,7 @@ class PromptServer():
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buffer.seek(0)
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return web.Response(body=buffer.read(), content_type=f'image/{image_format}',
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headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
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headers={"Content-Disposition": f"filename=\"{filename}\""})
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if 'channel' not in request.rel_url.query:
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channel = 'rgba'
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@ -580,7 +580,7 @@ class PromptServer():
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buffer.seek(0)
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return web.Response(body=buffer.read(), content_type='image/png',
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headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
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headers={"Content-Disposition": f"filename=\"{filename}\""})
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elif channel == 'a':
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with Image.open(file) as img:
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@ -597,7 +597,7 @@ class PromptServer():
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alpha_buffer.seek(0)
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return web.Response(body=alpha_buffer.read(), content_type='image/png',
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headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
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headers={"Content-Disposition": f"filename=\"{filename}\""})
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else:
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# Use the content type from asset resolution if available,
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# otherwise guess from the filename.
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@ -614,7 +614,7 @@ class PromptServer():
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return web.FileResponse(
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file,
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headers={
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"Content-Disposition": f"attachment; filename=\"{filename}\"",
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"Content-Disposition": f"filename=\"{filename}\"",
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"Content-Type": content_type
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}
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)
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