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Added a function line_to_prompt_dict() and removed duplicated initializations

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This commit is contained in:
Yuta Hayashibe
2023-10-29 19:57:25 +09:00
parent 01e00ac1b0
commit 291c29caaf
1 changed files with 61 additions and 63 deletions
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124
library/train_util.py
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@@ -4439,6 +4439,55 @@ def sample_images(*args, **kwargs):
return sample_images_common(StableDiffusionLongPromptWeightingPipeline, *args, **kwargs)
def line_to_prompt_dict(line: str) -> dict:
# subset of gen_img_diffusers
prompt_args = line.split(" --")
prompt_dict = {}
prompt_dict['prompt'] = prompt_args[0]
for parg in prompt_args:
try:
m = re.match(r"w (\d+)", parg, re.IGNORECASE)
if m:
prompt_dict['width'] = int(m.group(1))
continue
m = re.match(r"h (\d+)", parg, re.IGNORECASE)
if m:
prompt_dict['height'] = int(m.group(1))
continue
m = re.match(r"d (\d+)", parg, re.IGNORECASE)
if m:
prompt_dict['seed'] = int(m.group(1))
continue
m = re.match(r"s (\d+)", parg, re.IGNORECASE)
if m: # steps
prompt_dict['sample_steps'] = max(1, min(1000, int(m.group(1))))
continue
m = re.match(r"l ([\d\.]+)", parg, re.IGNORECASE)
if m: # scale
prompt_dict['scale'] = float(m.group(1))
continue
m = re.match(r"n (.+)", parg, re.IGNORECASE)
if m: # negative prompt
prompt_dict['negative_prompt'] = m.group(1)
continue
m = re.match(r"cn (.+)", parg, re.IGNORECASE)
if m: # negative prompt
prompt_dict['controlnet_image'] = m.group(1)
continue
except ValueError as ex:
print(f"Exception in parsing / 解析エラー: {parg}")
print(ex)
return prompt_dict
def sample_images_common(
pipe_class,
accelerator,
@@ -4517,73 +4566,22 @@ def sample_images_common(
with torch.no_grad():
# with accelerator.autocast():
for i, prompt in enumerate(prompts):
for i, prompt_dict in enumerate(prompts):
if not accelerator.is_main_process:
continue
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")
controlnet_image = prompt.get("controlnet_image")
prompt = prompt.get("prompt")
else:
# prompt = prompt.strip()
# if len(prompt) == 0 or prompt[0] == "#":
# continue
if isinstance(prompt_dict, str):
prompt_dict = line_to_prompt_dict(prompt_dict)
# 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
controlnet_image = 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
m = re.match(r"cn (.+)", parg, re.IGNORECASE)
if m: # negative prompt
controlnet_image = m.group(1)
continue
except ValueError as ex:
print(f"Exception in parsing / 解析エラー: {parg}")
print(ex)
assert isinstance(prompt_dict, dict)
negative_prompt = prompt_dict.get("negative_prompt")
sample_steps = prompt_dict.get("sample_steps", 30)
width = prompt_dict.get("width", 512)
height = prompt_dict.get("height", 512)
scale = prompt_dict.get("scale", 7.5)
seed = prompt_dict.get("seed")
controlnet_image = prompt_dict.get("controlnet_image")
prompt: str = prompt_dict.get("prompt", "")
if seed is not None:
torch.manual_seed(seed)