Merge branch 'concedo_experimental' into esocrok

Author: Nexesenex

expose.h

@@ -167,6 +167,9 @@ struct sd_load_model_inputs
     const int threads = 0;
     const int quant = 0;
     const bool flash_attention = false;
+    const bool offload_cpu = false;
+    const bool vae_cpu = false;
+    const bool clip_cpu = false;
     const bool diffusion_conv_direct = false;
     const bool vae_conv_direct = false;
     const bool taesd = false;
@@ -200,6 +203,8 @@ struct sd_generation_inputs
     const int seed = 0;
     const char * sample_method = nullptr;
     const int clip_skip = -1;
+    const int vid_req_frames = 1;
+    const int vid_req_avi = 0;
 };
 struct sd_generation_outputs
 {

kcpp_sdui.embd

@@ -289,6 +289,9 @@ class sd_load_model_inputs(ctypes.Structure):
                 ("threads", ctypes.c_int),
                 ("quant", ctypes.c_int),
                 ("flash_attention", ctypes.c_bool),
+                ("offload_cpu", ctypes.c_bool),
+                ("vae_cpu", ctypes.c_bool),
+                ("clip_cpu", ctypes.c_bool),
                 ("diffusion_conv_direct", ctypes.c_bool),
                 ("vae_conv_direct", ctypes.c_bool),
                 ("taesd", ctypes.c_bool),
@@ -320,7 +323,9 @@ class sd_generation_inputs(ctypes.Structure):
                 ("height", ctypes.c_int),
                 ("seed", ctypes.c_int),
                 ("sample_method", ctypes.c_char_p),
-                ("clip_skip", ctypes.c_int)]
+                ("clip_skip", ctypes.c_int),
+                ("vid_req_frames", ctypes.c_int),
+                ("vid_req_avi", ctypes.c_int)]
 
 class sd_generation_outputs(ctypes.Structure):
     _fields_ = [("status", ctypes.c_int),
@@ -1723,6 +1728,9 @@ def sd_load_model(model_filename,vae_filename,lora_filename,t5xxl_filename,clipl
     inputs.threads = thds
     inputs.quant = args.sdquant
     inputs.flash_attention = args.sdflashattention
+    inputs.offload_cpu = args.sdoffloadcpu
+    inputs.vae_cpu = args.sdvaecpu
+    inputs.clip_cpu = args.sdclipcpu
     sdconvdirect = sd_convdirect_option(args.sdconvdirect)
     inputs.diffusion_conv_direct = sdconvdirect == 'full'
     inputs.vae_conv_direct = sdconvdirect in ['vaeonly', 'full']
@@ -1830,6 +1838,9 @@ def sd_generate(genparams):
         seed = random.randint(100000, 999999)
     sample_method = genparams.get("sampler_name", "k_euler_a")
     clip_skip = tryparseint(genparams.get("clip_skip", -1),-1)
+    vid_req_frames = tryparseint(genparams.get("frames", 1),1)
+    vid_req_frames = 1 if (not vid_req_frames or vid_req_frames < 1) else vid_req_frames
+    vid_req_avi = 1 if genparams.get("avi_video", False) else 0
     extra_images_arr = genparams.get("extra_images", [])
     extra_images_arr = ([] if not extra_images_arr else extra_images_arr)
     extra_images_arr = [img for img in extra_images_arr if img not in (None, "")]
@@ -1861,6 +1872,8 @@ def sd_generate(genparams):
     inputs.seed = seed
     inputs.sample_method = sample_method.lower().encode("UTF-8")
     inputs.clip_skip = clip_skip
+    inputs.vid_req_frames = vid_req_frames
+    inputs.vid_req_avi = vid_req_avi
     ret = handle.sd_generate(inputs)
     outstr = ""
     if ret.status==1:
@@ -5697,6 +5710,9 @@ def hide_tooltip(event):
     sd_clipg_var = ctk.StringVar()
     sd_photomaker_var = ctk.StringVar()
     sd_flash_attention_var = ctk.IntVar(value=0)
+    sd_offload_cpu_var = ctk.IntVar(value=0)
+    sd_vae_cpu_var = ctk.IntVar(value=0)
+    sd_clip_cpu_var = ctk.IntVar(value=0)
     sd_vaeauto_var = ctk.IntVar(value=0)
     sd_tiled_vae_var = ctk.StringVar(value=str(default_vae_tile_threshold))
     sd_convdirect_var = ctk.StringVar(value=str(sd_convdirect_choices[0]))
@@ -6451,13 +6467,13 @@ def togglehorde(a,b,c):
     makefileentry(images_tab, "Image Gen. Model (safetensors/gguf):", "Select Image Gen Model File", sd_model_var, 1, width=280, singlecol=True, filetypes=[("*.safetensors *.gguf","*.safetensors *.gguf")], tooltiptxt="Select a .safetensors or .gguf Image Generation model file on disk to be loaded.")
     makelabelentry(images_tab, "Clamp Resolution Limit (Hard):", sd_clamped_var, 4, 50, padx=190,singleline=True,tooltip="Limit generation steps and output image size for shared use.\nSet to 0 to disable, otherwise value is clamped to the max size limit (min 512px).")
     makelabelentry(images_tab, "(Soft):", sd_clamped_soft_var, 4, 50, padx=290,singleline=True,tooltip="Square image size restriction, to protect the server against memory crashes.\nAllows width-height tradeoffs, eg. 640 allows 640x640 and 512x768\nLeave at 0 for the default value: 832 for SD1.5/SD2, 1024 otherwise.",labelpadx=250)
-    makelabelentry(images_tab, "Image Threads:" , sd_threads_var, 8, 50,padx=290,singleline=True,tooltip="How many threads to use during image generation.\nIf left blank, uses same value as threads.")
+    makelabelentry(images_tab, "ImgThreads:" , sd_threads_var, 8, 50,padx=290,singleline=True,tooltip="How many threads to use during image generation.\nIf left blank, uses same value as threads.",labelpadx=210)
     sd_model_var.trace_add("write", gui_changed_modelfile)
-    makelabelcombobox(images_tab, "Compress Weights (Saves Memory): ", sd_quant_var, 10, width=60, padx=220, labelpadx=8, tooltiptxt="Quantizes the SD model weights to save memory.\nHigher levels save more memory, and cause more quality degradation.", values=sd_quant_choices)
+    makelabelcombobox(images_tab, "Compress Weights: ", sd_quant_var, 8, width=60, padx=126, labelpadx=8, tooltiptxt="Quantizes the SD model weights to save memory.\nHigher levels save more memory, and cause more quality degradation.", values=sd_quant_choices)
     sd_quant_var.trace_add("write", changed_gpulayers_estimate)
 
-    makefileentry(images_tab, "Image LoRA (safetensors/gguf):", "Select SD lora file",sd_lora_var, 20, width=280, singlecol=True, filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD LoRA model file to be loaded. Should be unquantized!")
-    makelabelentry(images_tab, "Image LoRA Multiplier:" , sd_loramult_var, 22, 50,padx=290,singleline=True,tooltip="What mutiplier value to apply the SD LoRA with.")
+    makefileentry(images_tab, "Image LoRA:", "Select SD lora file",sd_lora_var, 20, width=160, singlerow=True, filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD LoRA model file to be loaded. Should be unquantized!")
+    makelabelentry(images_tab, "Multiplier:" , sd_loramult_var, 20, 50,padx=390,singleline=True,tooltip="What mutiplier value to apply the SD LoRA with.",labelpadx=330)
 
     makefileentry(images_tab, "T5-XXL File:", "Select Optional T5-XXL model file (SD3 or flux)",sd_t5xxl_var, 24, width=280, singlerow=True, filetypes=[("*.safetensors *.gguf","*.safetensors *.gguf")],tooltiptxt="Select a .safetensors t5xxl file to be loaded.")
     makefileentry(images_tab, "Clip-L File:", "Select Optional Clip-L model file (SD3 or flux)",sd_clipl_var, 26, width=280, singlerow=True, filetypes=[("*.safetensors *.gguf","*.safetensors *.gguf")],tooltiptxt="Select a .safetensors t5xxl file to be loaded.")
@@ -6478,7 +6494,10 @@ def toggletaesd(a,b,c):
     makecheckbox(images_tab, "TAE SD (AutoFix Broken VAE)", sd_vaeauto_var, 42,command=toggletaesd,tooltiptxt="Replace VAE with TAESD. May fix bad VAE.")
     makelabelcombobox(images_tab, "Conv2D Direct:", sd_convdirect_var, row=42, labelpadx=220, padx=310, width=90, tooltiptxt="Use Conv2D Direct operation. May save memory or improve performance.\nMight crash if not supported by the backend.\n", values=sd_convdirect_choices)
     makelabelentry(images_tab, "VAE Tiling Threshold:", sd_tiled_vae_var, 44, 50, padx=144,singleline=True,tooltip="Enable VAE Tiling for images above this size, to save memory.\nSet to 0 to disable VAE tiling.")
-    makecheckbox(images_tab, "SD Flash Attention", sd_flash_attention_var, 46, tooltiptxt="Enable Flash Attention for image diffusion. May save memory or improve performance.")
+    makecheckbox(images_tab, "SD Flash Attention", sd_flash_attention_var, 44,padx=230, tooltiptxt="Enable Flash Attention for image diffusion. May save memory or improve performance.")
+    makecheckbox(images_tab, "Model CPU Offload", sd_offload_cpu_var, 50,padx=8, tooltiptxt="Offload image weights in RAM to save VRAM, swap into VRAM when needed.")
+    makecheckbox(images_tab, "VAE on CPU", sd_vae_cpu_var, 50,padx=160, tooltiptxt="Force VAE to CPU only for image generation.")
+    makecheckbox(images_tab, "CLIP on CPU", sd_clip_cpu_var, 50,padx=280, tooltiptxt="Force CLIP to CPU only for image generation.")
 
     # audio tab
     audio_tab = tabcontent["Audio"]
@@ -6722,6 +6741,12 @@ def export_vars():
 
         if sd_flash_attention_var.get()==1:
             args.sdflashattention = True
+        if sd_offload_cpu_var.get()==1:
+            args.sdoffloadcpu = True
+        if sd_vae_cpu_var.get()==1:
+            args.sdvaecpu = True
+        if sd_clip_cpu_var.get()==1:
+            args.sdclipcpu = True
         args.sdthreads = (0 if sd_threads_var.get()=="" else int(sd_threads_var.get()))
         args.sdclamped = (0 if int(sd_clamped_var.get())<=0 else int(sd_clamped_var.get()))
         args.sdclampedsoft = (0 if int(sd_clamped_soft_var.get())<=0 else int(sd_clamped_soft_var.get()))
@@ -6964,6 +6989,9 @@ def import_vars(dict):
         sd_threads_var.set(str(dict["sdthreads"]) if ("sdthreads" in dict and dict["sdthreads"]) else str(default_threads))
         sd_quant_var.set(sd_quant_choices[(dict["sdquant"] if ("sdquant" in dict and dict["sdquant"]>=0 and dict["sdquant"]<len(sd_quant_choices)) else 0)])
         sd_flash_attention_var.set(1 if ("sdflashattention" in dict and dict["sdflashattention"]) else 0)
+        sd_offload_cpu_var.set(1 if ("sdoffloadcpu" in dict and dict["sdoffloadcpu"]) else 0)
+        sd_vae_cpu_var.set(1 if ("sdvaecpu" in dict and dict["sdvaecpu"]) else 0)
+        sd_clip_cpu_var.set(1 if ("sdclipcpu" in dict and dict["sdclipcpu"]) else 0)
         sd_convdirect_var.set(sd_convdirect_option(dict.get("sdconvdirect")))
         sd_vae_var.set(dict["sdvae"] if ("sdvae" in dict and dict["sdvae"]) else "")
         sd_t5xxl_var.set(dict["sdt5xxl"] if ("sdt5xxl" in dict and dict["sdt5xxl"]) else "")
@@ -8832,6 +8860,9 @@ def range_checker(arg: str):
     sdparsergroup.add_argument("--sdclipg", metavar=('[filename]'), help="Specify a Clip-G safetensors model for use in SD3. Leave blank if prebaked or unused.", default="")
     sdparsergroup.add_argument("--sdphotomaker", metavar=('[filename]'), help="PhotoMaker is a model that allows face cloning. Specify a PhotoMaker safetensors model which will be applied replacing img2img. SDXL models only. Leave blank if unused.", default="")
     sdparsergroup.add_argument("--sdflashattention", help="Enables Flash Attention for image generation.", action='store_true')
+    sdparsergroup.add_argument("--sdoffloadcpu", help="Offload image weights in RAM to save VRAM, swap into VRAM when needed.", action='store_true')
+    sdparsergroup.add_argument("--sdvaecpu", help="Force VAE to CPU only for image generation.", action='store_true')
+    sdparsergroup.add_argument("--sdclipcpu", help="Force CLIP to CPU only for image generation.", action='store_true')
     sdparsergroup.add_argument("--sdconvdirect", help="Enables Conv2D Direct. May improve performance or reduce memory usage. Might crash if not supported by the backend. Can be 'off' (default) to disable, 'full' to turn it on for all operations, or 'vaeonly' to enable only for the VAE.", type=sd_convdirect_option, choices=sd_convdirect_choices, default=sd_convdirect_choices[0])
     sdparsergroupvae = sdparsergroup.add_mutually_exclusive_group()
     sdparsergroupvae.add_argument("--sdvae", metavar=('[filename]'), help="Specify an image generation safetensors VAE which replaces the one in the model.", default="")