Claude
c6910ab775
Weight syntax: - Grammar: `(arg:SIGNED_NUMBER)` parses to a WeightedGroup - emph(text|w) is a function-style alias for the same - Nested weights multiply: ((cat:1.2):0.5) -> 0.6, matching A1111 - Weights are emitted in the (token, weight) tuples that comfy's stock encode_token_weights already applies post-transformer To make per-position weight indexing work, rows are now always exactly max_length entries: a multi-slot Action emits as one (action, w) entry followed by (ACTION_CONTINUATION, w) placeholders that process_tokens drops before handing to super().process_tokens. This replaces the previous variable-length-row + padding-math. PromptLang Inspect: - New node: CLIP + text -> STRING report of per-slot weight, L2 norm, and top-k nearest vocab tokens for the resolved embedding - lib/inspect.py uses the wrapper's stored attr name (cond.clip / tok.clip) rather than hardcoding 'clip_l', and uses the tokenizer's inv_vocab for decode Fix: parse_numeric_arg now rejects WeightedGroup (was only Action). SegOrAction widened to include WeightedGroup.
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
from typing import List
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from lark import Token, Transformer
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from comfy.sd1_clip import SDTokenizer
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from ..actions.action_utils import parse_numeric_arg
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from ..actions.base import Action, ActionArity
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from ..actions.weighted import WeightedGroup
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from .prompt_segment import PromptSegment
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from .registration import get_action_by_name
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from .utils import build_prompt_segment
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class PromptTransformer(Transformer):
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"""Maps the Lark parse tree into a flat list of PromptSegments and Actions."""
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def __init__(self, tokenizer: SDTokenizer):
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super().__init__()
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self.tokenizer = tokenizer
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def item(self, items: List[Token]):
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for item in items:
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if isinstance(item, (Action, PromptSegment, WeightedGroup)):
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return item
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if item.type == "WORD":
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return build_prompt_segment(str(item), self.tokenizer)
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if item.type == "QUOTED_STRING":
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# Strip surrounding quotes, unescape \" and \'.
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unquoted = item[1:-1]
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unescaped = unquoted.replace('\\"', '"').replace("\\'", "'")
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return build_prompt_segment(unescaped, self.tokenizer)
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raise ValueError(f"Unknown item type: {item.type}")
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def arg(self, items):
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return items
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def weighted(self, items):
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arg_items, weight_token = items
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return WeightedGroup(arg_items, float(weight_token))
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def embedding(self, items):
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return build_prompt_segment(
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f"{self.tokenizer.embedding_identifier}{items[0]}",
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self.tokenizer,
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)
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def generic_function(self, items):
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# `emph(text|w)` is sugar for `(text:w)`; handled here so it doesn't need
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# to fit the Action ABC (it changes weights, not embeddings).
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if str(items[0]) == "emph":
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if len(items) != 3:
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raise ValueError("emph expects exactly two arguments: emph(text|weight)")
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weight = parse_numeric_arg(items[2], action_name="emph", role="weight", cast=float)
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return WeightedGroup(items[1], weight)
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action = get_action_by_name(items[0])
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if action.arity == ActionArity.SINGLE:
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if len(items) != 2:
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raise ValueError(f"Action {action.action_name} expects exactly one argument")
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return action(items[1])
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if action.arity == ActionArity.MULTI:
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return action(items[1:])
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raise ValueError(f"Unknown action arity: {action.arity}")
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