Merge pull request #3068 from Disty0/dev

Update defaults and add autodetect for VRAM optimizations

installer.py

@@ -545,8 +545,10 @@ def check_torch():
     elif allow_ipex and (args.use_ipex or shutil.which('sycl-ls') is not None or shutil.which('sycl-ls.exe') is not None or os.environ.get('ONEAPI_ROOT') is not None or os.path.exists('/opt/intel/oneapi') or os.path.exists("C:/Program Files (x86)/Intel/oneAPI") or os.path.exists("C:/oneAPI")):
         args.use_ipex = True # pylint: disable=attribute-defined-outside-init
         log.info('Intel OneAPI Toolkit detected')
-        os.environ.setdefault('NEOReadDebugKeys', '1')
-        os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
+        if os.environ.get("NEOReadDebugKeys", None) is None:
+            os.environ.setdefault('NEOReadDebugKeys', '1')
+        if os.environ.get("ClDeviceGlobalMemSizeAvailablePercent", None) is None:
+            os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
         if "linux" in sys.platform:
             torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0.post0 torchvision==0.16.0.post0 intel-extension-for-pytorch==2.1.20+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
             os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow==2.15.0 intel-extension-for-tensorflow[xpu]==2.15.0.0')

modules/sd_models.py

@@ -709,13 +709,13 @@ def set_diffuser_options(sd_model, vae = None, op: str = 'model'):
             sd_model.enable_sequential_cpu_offload()
             sd_model.has_accelerate = True
     if hasattr(sd_model, "enable_vae_slicing"):
-        if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_slicing:
+        if shared.opts.diffusers_vae_slicing:
             shared.log.debug(f'Setting {op}: enable VAE slicing')
             sd_model.enable_vae_slicing()
         else:
             sd_model.disable_vae_slicing()
     if hasattr(sd_model, "enable_vae_tiling"):
-        if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_tiling:
+        if shared.opts.diffusers_vae_tiling:
             shared.log.debug(f'Setting {op}: enable VAE tiling')
             sd_model.enable_vae_tiling()
         else:

modules/shared.py

@@ -19,6 +19,7 @@ from modules.paths import models_path, script_path, data_path, sd_configs_path,
 from modules.dml import memory_providers, default_memory_provider, directml_do_hijack
 from modules.onnx_impl import initialize_onnx, execution_providers
 from modules.zluda import initialize_zluda
+from modules.memstats import memory_stats
 import modules.interrogate
 import modules.memmon
 import modules.styles
@@ -348,14 +349,31 @@ def temp_disable_extensions():
     return disabled
 
 
-if devices.backend == "cpu":
+if not (cmd_opts.lowvram or cmd_opts.medvram):
+    mem_stat = memory_stats()
+    if "gpu" in mem_stat:
+        if mem_stat['gpu']['total'] <= 4:
+            cmd_opts.lowvram = True
+            log.info(f"VRAM: Detected={mem_stat['gpu']['total']} GB Optimization=lowvram")
+        elif mem_stat['gpu']['total'] <= 8:
+            cmd_opts.medvram = True
+            log.info(f"VRAM: Detected={mem_stat['gpu']['total']} GB Optimization=medvram")
+        else:
+            log.info(f"VRAM: Detected={mem_stat['gpu']['total']} GB Optimization=none")
+
+
+if devices.backend == "directml": # Force BMM for DirectML instead of SDP
+    cross_attention_optimization_default = "Dynamic Attention BMM" if backend == Backend.DIFFUSERS else "Sub-quadratic"
+elif backend == Backend.DIFFUSERS and (cmd_opts.lowvram or cmd_opts.medvram):
+    cross_attention_optimization_default = "Dynamic Attention SDP"
+elif devices.backend == "cpu":
     cross_attention_optimization_default = "Scaled-Dot-Product" if backend == Backend.DIFFUSERS else "Doggettx's"
 elif devices.backend == "mps":
     cross_attention_optimization_default = "Scaled-Dot-Product" if backend == Backend.DIFFUSERS else "Doggettx's"
-elif devices.backend == "directml":
-    cross_attention_optimization_default = "Dynamic Attention BMM" if backend == Backend.DIFFUSERS else "Sub-quadratic"
 else: # cuda, rocm, ipex
     cross_attention_optimization_default ="Scaled-Dot-Product"
+
+
 if devices.backend == "rocm":
     sdp_options_default =  ['Memory attention', 'Math attention']
 #elif devices.backend == "zluda":
@@ -485,13 +503,13 @@ options_templates.update(options_section(('diffusers', "Diffusers Settings"), {
     "diffusers_move_base": OptionInfo(False, "Move base model to CPU when using refiner"),
     "diffusers_move_unet": OptionInfo(False, "Move base model to CPU when using VAE"),
     "diffusers_move_refiner": OptionInfo(False, "Move refiner model to CPU when not in use"),
-    "diffusers_extract_ema": OptionInfo(True, "Use model EMA weights when possible"),
+    "diffusers_extract_ema": OptionInfo(False, "Use model EMA weights when possible"),
     "diffusers_generator_device": OptionInfo("GPU", "Generator device", gr.Radio, {"choices": ["GPU", "CPU", "Unset"]}),
-    "diffusers_model_cpu_offload": OptionInfo(False, "Model CPU offload (--medvram)"),
-    "diffusers_seq_cpu_offload": OptionInfo(False, "Sequential CPU offload (--lowvram)"),
+    "diffusers_model_cpu_offload": OptionInfo(cmd_opts.medvram, "Model CPU offload (--medvram)"),
+    "diffusers_seq_cpu_offload": OptionInfo(cmd_opts.lowvram, "Sequential CPU offload (--lowvram)"),
     "diffusers_vae_upcast": OptionInfo("default", "VAE upcasting", gr.Radio, {"choices": ['default', 'true', 'false']}),
     "diffusers_vae_slicing": OptionInfo(True, "VAE slicing"),
-    "diffusers_vae_tiling": OptionInfo(False, "VAE tiling"),
+    "diffusers_vae_tiling": OptionInfo(cmd_opts.lowvram or cmd_opts.medvram, "VAE tiling"),
     "diffusers_model_load_variant": OptionInfo("default", "Preferred Model variant", gr.Radio, {"choices": ['default', 'fp32', 'fp16']}),
     "diffusers_vae_load_variant": OptionInfo("default", "Preferred VAE variant", gr.Radio, {"choices": ['default', 'fp32', 'fp16']}),
     "custom_diffusers_pipeline": OptionInfo('', 'Load custom Diffusers pipeline'),