modify the codes.

app.py

@@ -7,6 +7,8 @@ import os
 import torch
 import time
 from PIL import Image
+from cldm.hack import disable_verbosity, enable_sliced_attention
+from pytorch_lightning import seed_everything
 
 def process_multi_wrapper(rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3,
                             shared_prompt,  
@@ -104,7 +106,15 @@ def load_ckpt(model_ckpt = "LAION-Glyph-10M-Epoch-5"):
     allow_run_generation = False
     return output_str, None, allow_run_generation
 
-SAVE_MEMORY = True
+SAVE_MEMORY = False
+shared_seed = 0
+if shared_seed == -1:
+    shared_seed = random.randint(0, 65535)
+seed_everything(shared_seed)
+
+disable_verbosity()
+if SAVE_MEMORY:
+    enable_sliced_attention()
 cfg = OmegaConf.load("config.yaml")
 model = load_model_from_config(cfg, "laion10M_epoch_6_model_wo_ema.ckpt", verbose=True)
 # model = load_model_from_config(cfg, "model_wo_ema.ckpt", verbose=True)

ldm/modules/attention.py

@@ -15,7 +15,7 @@ try:
     XFORMERS_IS_AVAILBLE = True
 except:
     XFORMERS_IS_AVAILBLE = False
-
+# XFORMERS_IS_AVAILBLE = False
 DETERMISTIC = False
 
 def exists(val):

ldm/modules/diffusionmodules/model.py

@@ -15,7 +15,7 @@ try:
 except:
     XFORMERS_IS_AVAILBLE = False
     print("No module 'xformers'. Proceeding without it.")
-
+# XFORMERS_IS_AVAILBLE = False
 
 def get_timestep_embedding(timesteps, embedding_dim):
     """

scripts/rendertext_tool.py

@@ -2,9 +2,9 @@ from cldm.ddim_hacked import DDIMSampler
 import torch
 from annotator.render_images import render_text_image_custom
 from pytorch_lightning import seed_everything
-save_memory = False
-from cldm.hack import disable_verbosity
-disable_verbosity()
+# save_memory = False
+# from cldm.hack import disable_verbosity
+# disable_verbosity()
 import random
 import einops
 import numpy as np
@@ -95,6 +95,9 @@ class Render_Text:
             shared_eta, shared_a_prompt, shared_n_prompt,
             only_show_rendered_image=False
             ):
+        if shared_seed == -1:
+            shared_seed = random.randint(0, 65535)
+        seed_everything(shared_seed)
         with torch.no_grad(), \
             self.precision_scope("cuda"), \
             self.model.ema_scope("Sampling on Benchmark Prompts"):
@@ -136,9 +139,9 @@ class Render_Text:
                 
             H, W = shared_image_resolution, shared_image_resolution
 
-            if shared_seed == -1:
-                shared_seed = random.randint(0, 65535)
-            seed_everything(shared_seed)
+            # if shared_seed == -1:
+            #     shared_seed = random.randint(0, 65535)
+            # seed_everything(shared_seed)
 
             if torch.cuda.is_available() and self.save_memory:
                 print("low_vram_shift: is_diffusing", False)