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Better memory estimation for the SD/Flux VAE on AMD. (#10334)

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comfyanonymous
2025-10-13 19:37:19 -07:00
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parent e4ea393666
commit dfff7e5332
1 changed files with 7 additions and 2 deletions
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9
comfy/sd.py
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@@ -276,8 +276,13 @@ class VAE:
if 'decoder.up_blocks.0.resnets.0.norm1.weight' in sd.keys(): #diffusers format
sd = diffusers_convert.convert_vae_state_dict(sd)
self.memory_used_encode = lambda shape, dtype: (1767 * shape[2] * shape[3]) * model_management.dtype_size(dtype) #These are for AutoencoderKL and need tweaking (should be lower)
self.memory_used_decode = lambda shape, dtype: (2178 * shape[2] * shape[3] * 64) * model_management.dtype_size(dtype)
if model_management.is_amd():
VAE_KL_MEM_RATIO = 2.73
else:
VAE_KL_MEM_RATIO = 1.0
self.memory_used_encode = lambda shape, dtype: (1767 * shape[2] * shape[3]) * model_management.dtype_size(dtype) * VAE_KL_MEM_RATIO #These are for AutoencoderKL and need tweaking (should be lower)
self.memory_used_decode = lambda shape, dtype: (2178 * shape[2] * shape[3] * 64) * model_management.dtype_size(dtype) * VAE_KL_MEM_RATIO
self.downscale_ratio = 8
self.upscale_ratio = 8
self.latent_channels = 4