5.6 KiB
5.6 KiB
Documentation
- Class name: XY Input: Checkpoint
- Category: Efficiency Nodes/XY Inputs
- Output node: False
- Repo Ref: https://github.com/comfyanonymous/ComfyUI
TSC_XYplot_Checkpoint 节点专门用于处理与模型检查点相关的 XY 图数据。它主要关注验证和处理检查点值和剪辑跳过值，以便在模型训练和优化过程中进行效率分析。
Input types
Required
- target_ckpt
- 指定目标检查点类型，可以是'Base'或'Refiner'，用于确定 XY 图数据处理的上下文。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- input_mode
- 决定输入模式，影响检查点数据在 XY 图中的处理和可视化方式。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- batch_path
- 用于生成 XY 图的批处理数据文件路径，影响数据分析的来源。
- Comfy dtype: STRING
- Python dtype: str
- subdirectories
- 布尔值，表示是否在批处理数据搜索中包含子目录，扩大数据分析范围。
- Comfy dtype: BOOLEAN
- Python dtype: bool
- batch_sort
- 指定批处理数据的排序顺序，可以是'ascending'或'descending'，用于组织分析数据。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- batch_max
- 定义 XY 图要考虑的最大批次数，为数据分析设置上限。
- Comfy dtype: INT
- Python dtype: int
- ckpt_count
- 表示要包含在分析中的检查点数量，直接影响 XY 图的全面性。
- Comfy dtype: INT
- Python dtype: int
- ckpt_name_i
- 指定第 i 个检查点的名称，允许对 XY 图中包含的检查点数据进行详细自定义。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- clip_skip_i
- 确定第 i 个检查点的剪辑跳过值，影响每个检查点的数据分析粒度。
- Comfy dtype: INT
- Python dtype: int
- vae_name_i
- 识别第 i 个 VAE 模型的名称，使 XY 图分析中能够包含 VAE 特定数据。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
Output types
- X or Y
- 输出生成的 XY 图数据类型（'Clip Skip'或'Clip Skip (Refiner)'）以及相应的值，有助于效率分析。
- Comfy dtype: XY
- Python dtype: Tuple[str, List[int]]
Usage tips
- Infra type:
CPU - Common nodes: unknown
Source code
class TSC_XYplot_Checkpoint:
modes = ["Ckpt Names", "Ckpt Names+ClipSkip", "Ckpt Names+ClipSkip+VAE", "Checkpoint Batch"]
@classmethod
def INPUT_TYPES(cls):
checkpoints = ["None"] + folder_paths.get_filename_list("checkpoints")
vaes = ["Baked VAE"] + folder_paths.get_filename_list("vae")
inputs = {
"required": {
"target_ckpt": (["Base", "Refiner"],),
"input_mode": (cls.modes,),
"batch_path": ("STRING", {"default": xy_batch_default_path, "multiline": False}),
"subdirectories": ("BOOLEAN", {"default": False}),
"batch_sort": (["ascending", "descending"],),
"batch_max": ("INT", {"default": -1, "min": -1, "max": 50, "step": 1}),
"ckpt_count": ("INT", {"default": XYPLOT_DEF, "min": 0, "max": XYPLOT_LIM, "step": 1})
}
}
for i in range(1, XYPLOT_LIM+1):
inputs["required"][f"ckpt_name_{i}"] = (checkpoints,)
inputs["required"][f"clip_skip_{i}"] = ("INT", {"default": -1, "min": -24, "max": -1, "step": 1})
inputs["required"][f"vae_name_{i}"] = (vaes,)
return inputs
RETURN_TYPES = ("XY",)
RETURN_NAMES = ("X or Y",)
FUNCTION = "xy_value"
CATEGORY = "Efficiency Nodes/XY Inputs"
def xy_value(self, target_ckpt, input_mode, batch_path, subdirectories, batch_sort, batch_max, ckpt_count, **kwargs):
# Define XY type
xy_type = "Checkpoint" if target_ckpt == "Base" else "Refiner"
if "Batch" not in input_mode:
# Extract values from kwargs
checkpoints = [kwargs.get(f"ckpt_name_{i}") for i in range(1, ckpt_count + 1)]
clip_skips = [kwargs.get(f"clip_skip_{i}") for i in range(1, ckpt_count + 1)]
vaes = [kwargs.get(f"vae_name_{i}") for i in range(1, ckpt_count + 1)]
# Set None for Clip Skip and/or VAE if not correct modes
for i in range(ckpt_count):
if "ClipSkip" not in input_mode:
clip_skips[i] = None
if "VAE" not in input_mode:
vaes[i] = None
xy_value = [(checkpoint, clip_skip, vae) for checkpoint, clip_skip, vae in zip(checkpoints, clip_skips, vaes) if
checkpoint != "None"]
else:
if batch_max == 0:
return (None,)
try:
ckpts = get_batch_files(batch_path, CKPT_EXTENSIONS, include_subdirs=subdirectories)
if not ckpts:
print(f"{error('XY Plot Error:')} No Checkpoint files found.")
return (None,)
if batch_sort == "ascending":
ckpts.sort()
elif batch_sort == "descending":
ckpts.sort(reverse=True)
# Construct the xy_value using the obtained ckpts
xy_value = [(ckpt, None, None) for ckpt in ckpts]
if batch_max != -1: # If there's a limit
xy_value = xy_value[:batch_max]
except Exception as e:
print(f"{error('XY Plot Error:')} {e}")
return (None,)
return ((xy_type, xy_value),) if xy_value else (None,)