Cascade fix get_timestep_ratio_conditioning

Author: Disty0

installer.py

@@ -582,7 +582,7 @@ def install_ipex(torch_command):
 
 
 def install_openvino(torch_command):
-    check_python(supported_minors=[10,11], reason='IPEX backend requires Python 3.10 or 3.11')
+    check_python(supported_minors=[9, 10, 11], reason='OpenVINO backend requires Python 3.9, 3.10 or 3.11')
     log.info('Using OpenVINO')
     torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.2.0 torchvision==0.17.0 --index-url https://download.pytorch.org/whl/cpu')
     install(os.environ.get('OPENVINO_PACKAGE', 'openvino==2023.3.0'), 'openvino')

modules/model_stablecascade.py

@@ -1,7 +1,18 @@
 import os
 import copy
+import torch
 from modules import shared, devices
 
+def get_timestep_ratio_conditioning(t, alphas_cumprod):
+    s = torch.tensor([0.008]) # diffusers uses 0.003 while the original is 0.008
+    clamp_range = [0, 1]
+    min_var = torch.cos(s / (1 + s) * torch.pi * 0.5) ** 2
+    var = alphas_cumprod[t]
+    var = var.clamp(*clamp_range)
+    s, min_var = s.to(var.device), min_var.to(var.device)
+    ratio = (((var * min_var) ** 0.5).acos() / (torch.pi * 0.5)) * (1 + s) - s
+    return ratio
+
 def load_text_encoder(path):
     from transformers import CLIPTextConfig, CLIPTextModelWithProjection
     from accelerate.utils.modeling import set_module_tensor_to_device
@@ -125,6 +136,7 @@ def load_cascade_combined(checkpoint_info, diffusers_load_config):
 def cascade_post_load(sd_model):
     sd_model.prior_pipe.scheduler.config.clip_sample = False
     sd_model.default_scheduler = copy.deepcopy(sd_model.prior_pipe.scheduler)
+    sd_model.prior_pipe.get_timestep_ratio_conditioning = get_timestep_ratio_conditioning
     sd_model.decoder_pipe.text_encoder = sd_model.text_encoder = None  # Nothing uses the decoder's text encoder
     sd_model.prior_pipe.image_encoder = sd_model.prior_image_encoder = None # No img2img is implemented yet
     sd_model.prior_pipe.feature_extractor = sd_model.prior_feature_extractor = None # No img2img is implemented yet