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UVR.py

@@ -78,7 +78,7 @@ def get_execution_time(function, name):
     time_difference = end - start
     print(f'{name} Execution Time: ', time_difference)
 
-PREVIOUS_PATCH_WIN = 'UVR_Patch_9_25_23_2_1'
+PREVIOUS_PATCH_WIN = 'UVR_Patch_10_6_23_4_27'
 
 is_dnd_compatible = True
 banner_placement = -2
@@ -3228,7 +3228,7 @@ class MainWindow(TkinterDnD.Tk if is_dnd_compatible else tk.Tk):
         self.app_update_button = ttk.Button(settings_menu_main_Frame, textvariable=self.app_update_button_Text_var, width=SETTINGS_BUT_WIDTH-2, command=lambda:self.pop_up_update_confirmation())
         self.app_update_button.grid(pady=MENU_PADDING_1)
         
-        self.app_update_status_Label = tk.Label(settings_menu_main_Frame, textvariable=self.app_update_status_Text_var, font=(MAIN_FONT_NAME,  f"{FONT_SIZE_4}"), width=UPDATE_LABEL_WIDTH, justify="center", relief="ridge", fg="#13849f")
+        self.app_update_status_Label = tk.Label(settings_menu_main_Frame, textvariable=self.app_update_status_Text_var, padx=3, pady=3, font=(MAIN_FONT_NAME,  f"{FONT_SIZE_4}"), width=UPDATE_LABEL_WIDTH, justify="center", relief="ridge", fg="#13849f")
         self.app_update_status_Label.grid(pady=20)
         
         donate_Button = ttk.Button(settings_menu_main_Frame, image=self.donate_img, command=lambda:webbrowser.open_new_tab(DONATE_LINK_BMAC))

separate.py

@@ -117,7 +117,7 @@ class SeperateAttributes:
         self.main_model_primary = main_model_primary
         self.ensemble_primary_stem = model_data.ensemble_primary_stem
         self.is_multi_stem_ensemble = model_data.is_multi_stem_ensemble
-        self.is_gpu = False
+        self.is_mps = False
         self.is_deverb = True
         self.DENOISER_MODEL = model_data.DENOISER_MODEL
         self.DEVERBER_MODEL = model_data.DEVERBER_MODEL
@@ -137,6 +137,8 @@ class SeperateAttributes:
         self.stem_path_init = os.path.join(self.export_path, f'{self.audio_file_base}_({self.secondary_stem}).wav')
         self.deverb_vocal_opt = model_data.deverb_vocal_opt
         self.is_save_vocal_only = model_data.is_save_vocal_only
+        self.device = 'cpu'
+        self.run_type = ['CPUExecutionProvider']
         
         if self.is_inst_only_voc_splitter or self.is_sec_bv_rebalance:
             self.is_primary_stem_only = False
@@ -145,6 +147,14 @@ class SeperateAttributes:
         if main_model_primary and self.is_multi_stem_ensemble:
             self.primary_stem, self.secondary_stem = main_model_primary, secondary_stem(main_model_primary)
 
+        if self.is_gpu_conversion >= 0:
+            if OPERATING_SYSTEM == 'Darwin' and torch.backends.mps.is_available():
+                self.device = 'mps'
+                self.is_mps = True
+            elif torch.cuda.is_available():
+                self.device = 'cuda:0'
+                self.run_type = ['CUDAExecutionProvider']
+
         if model_data.process_method == MDX_ARCH_TYPE:
             self.is_mdx_ckpt = model_data.is_mdx_ckpt
             self.primary_model_name, self.primary_sources = self.cached_source_callback(MDX_ARCH_TYPE, model_name=self.model_basename)
@@ -170,13 +180,6 @@ class SeperateAttributes:
             self.dim_c = 4
             self.hop = 1024
 
-            if self.is_gpu_conversion >= 0 and torch.cuda.is_available():
-                self.is_gpu = True
-                self.device, self.run_type = torch.device('cuda:0'), ['CUDAExecutionProvider']
-            else:
-                self.is_gpu = False
-                self.device, self.run_type = torch.device('cpu'), ['CPUExecutionProvider']
-                
         if model_data.process_method == DEMUCS_ARCH_TYPE:
             self.demucs_stems = model_data.demucs_stems if not main_process_method in [MDX_ARCH_TYPE, VR_ARCH_TYPE] else None
             self.secondary_model_4_stem = model_data.secondary_model_4_stem
@@ -189,6 +192,7 @@ class SeperateAttributes:
             self.is_demucs_combine_stems = model_data.is_demucs_combine_stems
             self.demucs_stem_count = model_data.demucs_stem_count
             self.pre_proc_model = model_data.pre_proc_model
+            self.device = 'cpu' if self.is_mps and not self.demucs_version == DEMUCS_V4 else self.device
 
             self.primary_stem = model_data.ensemble_primary_stem if process_data['is_ensemble_master'] else model_data.primary_stem
             self.secondary_stem = model_data.ensemble_secondary_stem if process_data['is_ensemble_master'] else model_data.secondary_stem
@@ -218,7 +222,6 @@ class SeperateAttributes:
             self.primary_model_name, self.primary_sources = self.cached_source_callback(DEMUCS_ARCH_TYPE, model_name=self.model_basename)
 
         if model_data.process_method == VR_ARCH_TYPE:
-            self.device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')
             self.check_label_secondary_stem_runs()
             self.primary_model_name, self.primary_sources = self.cached_source_callback(VR_ARCH_TYPE, model_name=self.model_basename)
             self.mp = model_data.vr_model_param
@@ -446,7 +449,7 @@ class SeperateMDX(SeperateAttributes):
                 separator = MdxnetSet.ConvTDFNet(**model_params)
                 self.model_run = separator.load_from_checkpoint(self.model_path).to(self.device).eval()
             else:
-                if self.mdx_segment_size == self.dim_t:
+                if self.mdx_segment_size == self.dim_t and not self.is_mps:
                     ort_ = ort.InferenceSession(self.model_path, providers=self.run_type)
                     self.model_run = lambda spek:ort_.run(None, {'input': spek.cpu().numpy()})[0]
                 else:
@@ -786,11 +789,6 @@ class SeperateDemucs(SeperateAttributes):
         mix = prepare_mix(self.audio_file)
 
         if is_no_cache:
-            if self.is_gpu_conversion >= 0:
-                self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu') 
-            else:
-                self.device = torch.device('cpu')
-            
             if self.demucs_version == DEMUCS_V1:
                 if str(self.model_path).endswith(".gz"):
                     self.model_path = gzip.open(self.model_path, "rb")
@@ -1002,13 +1000,8 @@ class SeperateVR(SeperateAttributes):
             self.load_cached_sources()
         else:
             self.start_inference_console_write()
-            if self.is_gpu_conversion >= 0:
+
-                if OPERATING_SYSTEM == 'Darwin':
+            device = self.device
-                    device = torch.device('mps' if torch.backends.mps.is_available() else 'cpu')
-                else:
-                    device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu') 
-            else:
-                device = torch.device('cpu')
 
             nn_arch_sizes = [
                 31191, # default