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tune attn params

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layerdiffusion
2024-08-02 04:18:47 -07:00
parent e5860a4999
commit 76e0d17af3
3 changed files with 15 additions and 30 deletions
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17
backend/modules/k_model.py
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@@ -1,6 +1,6 @@
import torch
from backend import memory_management
from backend import memory_management, attention
from backend.modules.k_prediction import k_prediction_from_diffusers_scheduler
@@ -41,14 +41,11 @@ class KModel(torch.nn.Module):
area = input_shape[0] * input_shape[2] * input_shape[3]
dtype_size = memory_management.dtype_size(self.computation_dtype)
scaler = 1.28
# TODO: Consider these again
# if ldm_patched.modules.model_management.xformers_enabled() or ldm_patched.modules.model_management.pytorch_attention_flash_attention():
# scaler = 1.28
# else:
# scaler = 1.65
# if ldm_patched.ldm.modules.attention._ATTN_PRECISION == "fp32":
# dtype_size = 4
if attention.attention_function in [attention.attention_pytorch, attention.attention_xformers]:
scaler = 1.28
else:
scaler = 1.65
if attention.get_attn_precision() == torch.float32:
dtype_size = 4
return scaler * area * dtype_size * 16384