Merge pull request #504 from Linaqruf/main

TOML support for sample prompt
kohya-ss · May 15, 2023 · b556fc4 · b556fc4
2 parents 99f4940 + 8ab5c8c
commit b556fc4
Showing 1 changed file with 72 additions and 49 deletions.
diff --git a/library/train_util.py b/library/train_util.py
@@ -3291,9 +3291,22 @@ def sample_images(
     vae.to(device)
 
     # read prompts
-    with open(args.sample_prompts, "rt", encoding="utf-8") as f:
-        prompts = f.readlines()
 
+    # with open(args.sample_prompts, "rt", encoding="utf-8") as f:
+    #     prompts = f.readlines()
+
+    if args.sample_prompts.endswith('.txt'):
+        with open(args.sample_prompts, 'r') as f:
+            lines = f.readlines()
+        prompts = [line.strip() for line in lines if len(line.strip()) > 0 and line[0] != "#"]
+    elif args.sample_prompts.endswith('.toml'):
+        with open(args.sample_prompts, 'r') as f:
+            data = toml.load(f)
+        prompts = [dict(**data['prompt'], **subset) for subset in data['prompt']['subset']]
+    elif args.sample_prompts.endswith('.json'):
+        with open(args.sample_prompts, 'r') as f:
+            prompts = json.load(f)
+
     # schedulerを用意する
     sched_init_args = {}
     if args.sample_sampler == "ddim":
@@ -3362,53 +3375,63 @@ def sample_images(
             for i, prompt in enumerate(prompts):
                 if not accelerator.is_main_process:
                     continue
-                prompt = prompt.strip()
-                if len(prompt) == 0 or prompt[0] == "#":
-                    continue
-
-                # subset of gen_img_diffusers
-                prompt_args = prompt.split(" --")
-                prompt = prompt_args[0]
-                negative_prompt = None
-                sample_steps = 30
-                width = height = 512
-                scale = 7.5
-                seed = None
-                for parg in prompt_args:
-                    try:
-                        m = re.match(r"w (\d+)", parg, re.IGNORECASE)
-                        if m:
-                            width = int(m.group(1))
-                            continue
-
-                        m = re.match(r"h (\d+)", parg, re.IGNORECASE)
-                        if m:
-                            height = int(m.group(1))
-                            continue
-
-                        m = re.match(r"d (\d+)", parg, re.IGNORECASE)
-                        if m:
-                            seed = int(m.group(1))
-                            continue
-
-                        m = re.match(r"s (\d+)", parg, re.IGNORECASE)
-                        if m:  # steps
-                            sample_steps = max(1, min(1000, int(m.group(1))))
-                            continue
-
-                        m = re.match(r"l ([\d\.]+)", parg, re.IGNORECASE)
-                        if m:  # scale
-                            scale = float(m.group(1))
-                            continue
-
-                        m = re.match(r"n (.+)", parg, re.IGNORECASE)
-                        if m:  # negative prompt
-                            negative_prompt = m.group(1)
-                            continue
-
-                    except ValueError as ex:
-                        print(f"Exception in parsing / 解析エラー: {parg}")
-                        print(ex)
+
+                if isinstance(prompt, dict):
+                    negative_prompt = prompt.get("negative_prompt")
+                    sample_steps = prompt.get("sample_steps", 30)
+                    width = prompt.get("width", 512)
+                    height = prompt.get("height", 512)
+                    scale = prompt.get("scale", 7.5)
+                    seed = prompt.get("seed")
+                    prompt = prompt.get("prompt")
+                else:               
+                    # prompt = prompt.strip()
+                    # if len(prompt) == 0 or prompt[0] == "#":
+                    #     continue
+
+                    # subset of gen_img_diffusers
+                    prompt_args = prompt.split(" --")
+                    prompt = prompt_args[0]
+                    negative_prompt = None
+                    sample_steps = 30
+                    width = height = 512
+                    scale = 7.5
+                    seed = None
+                    for parg in prompt_args:
+                        try:
+                            m = re.match(r"w (\d+)", parg, re.IGNORECASE)
+                            if m:
+                                width = int(m.group(1))
+                                continue
+
+                            m = re.match(r"h (\d+)", parg, re.IGNORECASE)
+                            if m:
+                                height = int(m.group(1))
+                                continue
+
+                            m = re.match(r"d (\d+)", parg, re.IGNORECASE)
+                            if m:
+                                seed = int(m.group(1))
+                                continue
+
+                            m = re.match(r"s (\d+)", parg, re.IGNORECASE)
+                            if m:  # steps
+                                sample_steps = max(1, min(1000, int(m.group(1))))
+                                continue
+
+                            m = re.match(r"l ([\d\.]+)", parg, re.IGNORECASE)
+                            if m:  # scale
+                                scale = float(m.group(1))
+                                continue
+
+                            m = re.match(r"n (.+)", parg, re.IGNORECASE)
+                            if m:  # negative prompt
+                                negative_prompt = m.group(1)
+                                continue
+
+                        except ValueError as ex:
+                            print(f"Exception in parsing / 解析エラー: {parg}")
+                            print(ex)
 
                 if seed is not None:
                     torch.manual_seed(seed)