From 9d5c5199ad5fdc45400f0ec12478c3aa26cd47e9 Mon Sep 17 00:00:00 2001 From: Ruinan Date: Thu, 25 Sep 2025 19:28:31 +0800 Subject: [PATCH] Delete ComfyUI_PromptTool/nodes.py Delete the incorrect file --- ComfyUI_PromptTool/nodes.py | 288 ------------------------------------ 1 file changed, 288 deletions(-) delete mode 100644 ComfyUI_PromptTool/nodes.py diff --git a/ComfyUI_PromptTool/nodes.py b/ComfyUI_PromptTool/nodes.py deleted file mode 100644 index 27d0920..0000000 --- a/ComfyUI_PromptTool/nodes.py +++ /dev/null @@ -1,288 +0,0 @@ -import json -import os -import hashlib -import time -import torch -import torch.nn.functional as F - -""" -最简批量帧文本编码（仅正向），增强兼容性： -- 解决：不同 prompt 生成的 cond 长度不一致导致 torch.cat 报错 -> 统一 padding -- 解决：某些 clip.encode_from_tokens 在 return_pooled=True 时返回 (cond, None) 或根本不支持 pooled 的情况 -- 若 pooled 全部为 None，则不放 pooled_output 或放占位空字符串 -""" - -def parse_frame_prompts(raw_text: str): - """ - 解析输入为 {frame_index: prompt} 的升序字典。 - 允许缺少最外层 {}；允许末尾多余逗号。 - """ - txt = raw_text.strip() - if not txt: - return {} - if not txt.startswith("{"): - txt = "{" + txt - if not txt.endswith("}"): - txt = txt + "}" - txt = txt.replace(",}", "}") - data = json.loads(txt) - out = {} - for k, v in data.items(): - try: - idx = int(k) - except: - continue - # 非数字 key 忽略 - out[idx] = str(v) - return dict(sorted(out.items(), key=lambda x: x[0])) - - -def encode_prompts_sequential(clip, ordered_items): - """ - 逐条编码；对 cond 做长度统一；pooled 可能为 None。 - ordered_items: List[(frame_index, prompt)] - 返回: cond_final, pooled_final(或 None), has_pooled(bool) - """ - cond_list = [] - pooled_list = [] - pooled_available = True # 先假设有 pooled - max_tokens = 0 - - with torch.no_grad(): - for frame_idx, prompt in ordered_items: - tokens = clip.tokenize(prompt) - # 兼容：有的实现如果 return_pooled=True 仍返回单值 - enc = clip.encode_from_tokens(tokens, return_pooled=True) - if isinstance(enc, (list, tuple)) and len(enc) == 2: - cond, pooled = enc - else: - cond, pooled = enc, None - - if cond.dim() != 3: - # 期望 shape: [B(=1), T, C]; 若是 [T, C] 补一个 batch 维 - if cond.dim() == 2: - cond = cond.unsqueeze(0) - else: - raise ValueError(f"Unexpected cond tensor shape: {cond.shape}") - - if cond.shape[1] > max_tokens: - max_tokens = cond.shape[1] - - cond_list.append(cond) - - if pooled is None: - pooled_available = False - pooled_list.append(None) - else: - # 期望 [B(=1), D] 或 [D]; 若 [D] -> [1,D] - if pooled.dim() == 1: - pooled = pooled.unsqueeze(0) - pooled_list.append(pooled) - - if not cond_list: - dummy = torch.zeros(1, 1) - return dummy, None, False - - # 对 cond 做 padding - padded = [] - for c in cond_list: - if c.shape[1] < max_tokens: - pad_len = max_tokens - c.shape[1] - # shape [1, T, C]，pad 第二维 (tokens)：(last_dim_left, last_dim_right, second_dim_left, second_dim_right) - c = F.pad(c, (0, 0, 0, pad_len)) - padded.append(c) - cond_final = torch.cat(padded, dim=0) # [N, max_tokens, C] - - pooled_final = None - if pooled_available: - # 校验 pooled 维度并 cat - processed = [] - for p in pooled_list: - if p is None: - pooled_available = False - break - if p.dim() == 1: - p = p.unsqueeze(0) - processed.append(p) - if pooled_available and processed: - try: - pooled_final = torch.cat(processed, dim=0) # [N, D] - except Exception: - # 如果维度不一致，放弃 pooled - pooled_final = None - pooled_available = False - - return cond_final, pooled_final, pooled_available - - -## 删除了 BatchPrompt 节点，保留 PromptQueue - - -def _read_lines_from_source(multiline_text: str, file_path: str = "", use_file: bool = False): - """ - 从多行文本或文件读取，每行一个提示词；自动去除空行和首尾空白。 - """ - lines = [] - if use_file and file_path: - try: - with open(file_path, "r", encoding="utf-8", errors="ignore") as f: - lines = f.readlines() - except Exception: - # 回退到多行文本 - lines = multiline_text.splitlines() - else: - lines = multiline_text.splitlines() - - cleaned = [] - for raw in lines: - s = str(raw).strip() - if not s: - continue - cleaned.append(s) - return cleaned - - -def _apply_template_to_lines(lines, template: str): - """ - 将每行替换进模板。若模板为空或不含 {p}，则直接返回行本身。 - """ - if not template or "{p}" not in template: - return lines - return [template.replace("{p}", line) for line in lines] - - -class PromptQueue: - """ - 将多行提示词视为队列，或从 txt 文件读取（逐行）。 - 输出按批次堆叠的 CONDITIONING，便于一次性批量生成。 - 可选模板，将每行填充到模板中的 {prompt} 占位符。 - """ - @classmethod - def INPUT_TYPES(cls): - return { - "required": { - "clip": ("CLIP",), - "multiline_text": ("STRING", {"multiline": True, "default": "A cat\nA dog\nA bird"}), - "use_file": ("BOOLEAN", {"default": False}), - "file_path": ("STRING", {"multiline": False, "default": ""}), - "template": ("STRING", {"multiline": False, "default": "{p}"}), - "mode": (["all", "incremental"],), - "label": ("STRING", {"multiline": False, "default": "Prompt Queue 001"}), - } - } - - RETURN_TYPES = ("CONDITIONING",) - RETURN_NAMES = ("COND",) - FUNCTION = "run" - CATEGORY = "SimpleBatch" - - def run(self, clip, multiline_text, use_file, file_path, template, mode="all", label="Prompt Queue 001"): - lines = _read_lines_from_source(multiline_text, file_path, use_file) - lines = _apply_template_to_lines(lines, template) - - if not lines: - dummy = torch.zeros(1, 1) - return ([[dummy, {"pooled_output": ""}]],) - - # Mode: incremental consumes one line per call using a persistent counter per label - if mode == "incremental": - idx = _pq_get_next_index(label, _pq_total=len(lines), source_descriptor=_pq_source_descriptor(use_file, file_path, multiline_text)) - line = lines[idx] - ordered = [(0, line)] - cond, pooled, has_pooled = encode_prompts_sequential(clip, ordered) - meta = {"pooled_output": pooled if has_pooled and pooled is not None else ""} - return ([[cond, meta]],) - - # Default: all lines batched together - ordered = list(enumerate(lines)) - cond, pooled, has_pooled = encode_prompts_sequential(clip, ordered) - meta = {"pooled_output": pooled if has_pooled and pooled is not None else ""} - return ([[cond, meta]],) - - @classmethod - def IS_CHANGED(cls, clip, multiline_text, use_file, file_path, template, mode="all", label="Prompt Queue 001"): - # Ensure incremental mode re-executes each time to advance the queue - if mode == "incremental": - return str(time.time()) - # For deterministic modes, hash inputs so caching works as expected - try: - desc = _pq_source_descriptor(bool(use_file), str(file_path), str(multiline_text)) - key = f"{desc}|{template}" - return hashlib.sha1(key.encode("utf-8", errors="ignore")).hexdigest() - except Exception: - return "" - - -# --- Persistent queue state (per label) --- -class _JsonKVStore: - def __init__(self, file_path: str): - self.file_path = file_path - self.data = {} - self._load() - - def _load(self): - try: - if os.path.exists(self.file_path): - with open(self.file_path, "r", encoding="utf-8") as f: - self.data = json.load(f) - else: - self.data = {} - except Exception: - self.data = {} - - def _save(self): - try: - os.makedirs(os.path.dirname(self.file_path), exist_ok=True) - with open(self.file_path, "w", encoding="utf-8") as f: - json.dump(self.data, f, indent=2) - except Exception: - pass - - def get(self, category: str, key: str, default=None): - return self.data.get(category, {}).get(key, default) - - def put(self, category: str, key: str, value) -> None: - if category not in self.data: - self.data[category] = {} - self.data[category][key] = value - self._save() - - -_pq_state_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "_prompt_queue_state") -_pq_store = _JsonKVStore(os.path.join(_pq_state_dir, "state.json")) - - -def _pq_source_descriptor(use_file: bool, file_path: str, multiline_text: str) -> str: - if use_file and file_path: - try: - return "FILE:" + os.path.abspath(file_path) - except Exception: - return "FILE:" + file_path - # Text hash as descriptor; content changes won't reset index to allow continuing when appending - h = hashlib.sha1(multiline_text.encode("utf-8", errors="ignore")).hexdigest() - return "TEXT:" + h - - -def _pq_get_next_index(label: str, _pq_total: int, source_descriptor: str) -> int: - if _pq_total <= 0: - return 0 - # Reset only when source type switches between FILE and TEXT, or file path changes - stored_src = _pq_store.get("PromptQueue Sources", label, None) - if stored_src != source_descriptor: - _pq_store.put("PromptQueue Sources", label, source_descriptor) - _pq_store.put("PromptQueue Counters", label, 0) - - current = _pq_store.get("PromptQueue Counters", label, 0) or 0 - next_index = current % _pq_total - _pq_store.put("PromptQueue Counters", label, (current + 1) % _pq_total) - return next_index - - -# 注册新节点 -NODE_CLASS_MAPPINGS.update({ - "PromptQueue": PromptQueue, -}) - -NODE_DISPLAY_NAME_MAPPINGS.update({ - "PromptQueue": "Prompt Queue", -}) \ No newline at end of file