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unified logger

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This commit is contained in:
Vladimir Mandic
2026-02-19 09:46:42 +01:00
parent bfe014f5da
commit a3074baf8b
315 changed files with 2507 additions and 2116 deletions
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modules/prompt_parser_diffusers.py
+7 -6
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@@ -6,10 +6,11 @@ import torch
from compel.embeddings_provider import BaseTextualInversionManager, EmbeddingsProvider
from transformers import PreTrainedTokenizer
from modules import shared, prompt_parser, devices, sd_models
from modules import logger
from modules.prompt_parser_xhinker import get_weighted_text_embeddings_sd15, get_weighted_text_embeddings_sdxl_2p, get_weighted_text_embeddings_sd3, get_weighted_text_embeddings_flux1, get_weighted_text_embeddings_chroma
debug_enabled = os.environ.get('SD_PROMPT_DEBUG', None)
debug = shared.log.trace if debug_enabled else lambda *args, **kwargs: None
debug = logger.log.trace if debug_enabled else lambda *args, **kwargs: None
debug('Trace: PROMPT')
orig_encode_token_ids_to_embeddings = EmbeddingsProvider._encode_token_ids_to_embeddings # pylint: disable=protected-access
token_dict = None # used by helper get_tokens
@@ -29,7 +30,7 @@ def prompt_compatible(pipe = None):
'Chroma' not in pipe.__class__.__name__ and
'HiDreamImage' not in pipe.__class__.__name__
):
shared.log.warning(f"Prompt parser not supported: {pipe.__class__.__name__}")
logger.log.warning(f"Prompt parser not supported: {pipe.__class__.__name__}")
return False
return True
@@ -80,7 +81,7 @@ class PromptEmbedder:
return
self.pipe = prepare_model(p.sd_model)
if self.pipe is None:
shared.log.error("Prompt encode: cannot find text encoder in model")
logger.log.error("Prompt encode: cannot find text encoder in model")
return
seen_prompts = {}
# per prompt in batch
@@ -295,7 +296,7 @@ class PromptEmbedder:
res = pad_to_same_length(self.pipe, res)
return torch.cat(res)
except Exception as e:
shared.log.error(f"Prompt encode: {e}")
logger.log.error(f"Prompt encode: {e}")
return None
@@ -419,7 +420,7 @@ def get_tokens(pipe, msg, prompt):
added_tokens = getattr(tokenizer, 'added_tokens_decoder', {})
for k, v in added_tokens.items():
token_dict[str(v)] = k
shared.log.debug(f'Tokenizer: words={len(token_dict)} file="{fn}"')
logger.log.debug(f'Tokenizer: words={len(token_dict)} file="{fn}"')
has_bos_token = getattr(tokenizer, 'bos_token_id', None) is not None
has_eos_token = getattr(tokenizer, 'eos_token_id', None) is not None
try:
@@ -636,7 +637,7 @@ def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", c
embedding_providers = prepare_embedding_providers(pipe, clip_skip)
if len(embedding_providers) == 0:
shared.log.error("Prompt encode: cannot find text encoder in model")
logger.log.error("Prompt encode: cannot find text encoder in model")
return None, None, None, None, None, None
empty_embedding_providers = None
if 'StableCascade' in pipe.__class__.__name__: