Added Model rescale and prepared a release upgrade

jobs/process/TrainSliderProcess.py

@@ -46,8 +46,8 @@ class EncodedPromptPair:
             negative_target,
             negative_target_with_neutral,
             neutral,
-            both_targets,
             empty_prompt,
+            both_targets,
             action=ACTION_TYPES_SLIDER.ERASE_NEGATIVE,
             multiplier=1.0,
             weight=1.0
@@ -123,23 +123,24 @@ class TrainSliderProcess(BaseSDTrainProcess):
         self.print(f"Loading prompt file from {self.slider_config.prompt_file}")
 
         # read line by line from file
-        with open(self.slider_config.prompt_file, 'r') as f:
-            self.prompt_txt_list = f.readlines()
-            # clean empty lines
-            self.prompt_txt_list = [line.strip() for line in self.prompt_txt_list if len(line.strip()) > 0]
+        if self.slider_config.prompt_file:
+            with open(self.slider_config.prompt_file, 'r') as f:
+                self.prompt_txt_list = f.readlines()
+                # clean empty lines
+                self.prompt_txt_list = [line.strip() for line in self.prompt_txt_list if len(line.strip()) > 0]
 
-        self.print(f"Loaded {len(self.prompt_txt_list)} prompts. Encoding them..")
+            self.print(f"Loaded {len(self.prompt_txt_list)} prompts. Encoding them..")
+
+
+            if not self.slider_config.prompt_tensors:
+                # shuffle
+                random.shuffle(self.prompt_txt_list)
+                # trim to max steps
+                self.prompt_txt_list = self.prompt_txt_list[:self.train_config.steps]
+                # trim list to our max steps
 
         cache = PromptEmbedsCache()
 
-        if not self.slider_config.prompt_tensors:
-            # shuffle
-            random.shuffle(self.prompt_txt_list)
-            # trim to max steps
-            self.prompt_txt_list = self.prompt_txt_list[:self.train_config.steps]
-            # trim list to our max steps
-
-
         # get encoded latents for our prompts
         with torch.no_grad():
             if self.slider_config.prompt_tensors is not None:
@@ -169,7 +170,9 @@ class TrainSliderProcess(BaseSDTrainProcess):
                 # encode empty_prompt
                 cache[empty_prompt] = self.sd.encode_prompt(empty_prompt)
 
-                for neutral in tqdm(self.prompt_txt_list, desc="Encoding prompts", leave=False):
+                neutral_list = self.prompt_txt_list if self.prompt_txt_list is not None else [""]
+
+                for neutral in tqdm(neutral_list, desc="Encoding prompts", leave=False):
                     for target in self.slider_config.targets:
                         prompt_list = [
                             f"{target.target_class}", # target_class
@@ -212,10 +215,15 @@ class TrainSliderProcess(BaseSDTrainProcess):
                     save_file(state_dict, self.slider_config.prompt_tensors)
 
             prompt_pairs = []
-            for neutral in tqdm(self.prompt_txt_list, desc="Encoding prompts", leave=False):
+            for neutral in tqdm(neutral_list, desc="Encoding prompts", leave=False):
                 for target in self.slider_config.targets:
+                    erase_negative = len(target.positive.strip()) == 0
+                    enhance_positive = len(target.negative.strip()) == 0
+
+                    both = not erase_negative and not enhance_positive
 
                     if both or erase_negative:
+                        print("Encoding erase negative")
                         prompt_pairs += [
                             # erase standard
                             EncodedPromptPair(
@@ -234,6 +242,7 @@ class TrainSliderProcess(BaseSDTrainProcess):
                             ),
                         ]
                     if both or enhance_positive:
+                        print("Encoding enhance positive")
                         prompt_pairs += [
                             # enhance standard, swap pos neg
                             EncodedPromptPair(
@@ -251,7 +260,9 @@ class TrainSliderProcess(BaseSDTrainProcess):
                                 weight=target.weight
                             ),
                         ]
-                    if both or enhance_positive:
+                    # if both or enhance_positive:
+                    if both:
+                        print("Encoding erase positive (inverse)")
                         prompt_pairs += [
                             # erase inverted
                             EncodedPromptPair(
@@ -269,7 +280,9 @@ class TrainSliderProcess(BaseSDTrainProcess):
                                 weight=target.weight
                             ),
                         ]
-                    if both or erase_negative:
+                    # if both or erase_negative:
+                    if both:
+                        print("Encoding enhance negative (inverse)")
                         prompt_pairs += [
                             # enhance inverted
                             EncodedPromptPair(
@@ -341,10 +354,6 @@ class TrainSliderProcess(BaseSDTrainProcess):
             torch.randint(0, len(self.slider_config.resolutions), (1,)).item()
         ]
 
-        target_class = prompt_pair.target_class
-        neutral = prompt_pair.neutral
-        negative = prompt_pair.negative_target
-        positive = prompt_pair.positive_target
         weight = prompt_pair.weight
         multiplier = prompt_pair.multiplier