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Integrate comfy-aimdo 0.2 which takes a different approach to installing the memory allocator hook. Instead of using the complicated and buggy pytorch MemPool+CudaPluggableAlloctor, cuda is directly hooked making the process much more transparent to both comfy and pytorch. As far as pytorch knows, aimdo doesnt exist anymore, and just operates behind the scenes. Remove all the mempool setup stuff for dynamic_vram and bump the comfy-aimdo version. Remove the allocator object from memory_management and demote its use as an enablment check to a boolean flag. Comfy-aimdo 0.2 also support the pytorch cuda async allocator, so remove the dynamic_vram based force disablement of cuda_malloc and just go back to the old settings of allocators based on command line input.
36 lines
494 B
Plaintext
36 lines
494 B
Plaintext
comfyui-frontend-package==1.39.14
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comfyui-workflow-templates==0.8.43
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comfyui-embedded-docs==0.4.1
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torch
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torchsde
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torchvision
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torchaudio
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numpy>=1.25.0
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einops
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transformers>=4.50.3
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tokenizers>=0.13.3
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sentencepiece
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safetensors>=0.4.2
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aiohttp>=3.11.8
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yarl>=1.18.0
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pyyaml
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Pillow
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scipy
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tqdm
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psutil
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alembic
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SQLAlchemy
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av>=14.2.0
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comfy-kitchen>=0.2.7
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comfy-aimdo>=0.2.0
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requests
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#non essential dependencies:
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kornia>=0.7.1
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spandrel
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pydantic~=2.0
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pydantic-settings~=2.0
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PyOpenGL
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PyOpenGL-accelerate
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glfw
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