Merge branch 'main' into fix/expected-torch-device

ldm/invoke/__init__.py

@@ -2,3 +2,12 @@ from ._version import __version__
 
 __app_id__= 'invoke-ai/InvokeAI'
 __app_name__= 'InvokeAI'
+
+
+def _ignore_xformers_triton_message_on_windows():
+    import logging
+    logging.getLogger("xformers").addFilter(
+        lambda record: 'A matching Triton is not available' not in record.getMessage())
+
+# In order to be effective, this needs to happen before anything could possibly import xformers.
+_ignore_xformers_triton_message_on_windows()

ldm/invoke/conditioning.py

@@ -93,7 +93,7 @@ def _get_conditioning_for_prompt(parsed_prompt: Union[Blend, FlattenedPrompt], p
     Process prompt structure and tokens, and return (conditioning, unconditioning, extra_conditioning_info)
     """
 
-    if log_tokens or Globals.log_tokenization:
+    if log_tokens or getattr(Globals, "log_tokenization", False):
         print(f"\n>> [TOKENLOG] Parsed Prompt: {parsed_prompt}")
         print(f"\n>> [TOKENLOG] Parsed Negative Prompt: {parsed_negative_prompt}")
 
@@ -236,7 +236,7 @@ def _get_embeddings_and_tokens_for_prompt(model, flattened_prompt: FlattenedProm
     fragments = [x.text for x in flattened_prompt.children]
     weights = [x.weight for x in flattened_prompt.children]
     embeddings, tokens = model.get_learned_conditioning([fragments], return_tokens=True, fragment_weights=[weights])
-    if log_tokens or Globals.log_tokenization:
+    if log_tokens or getattr(Globals, "log_tokenization", False):
         text = " ".join(fragments)
         log_tokenization(text, model, display_label=log_display_label)
 
@@ -296,4 +296,4 @@ def log_tokenization(text, model, display_label=None):
     
     if discarded != "":
         print(f'\n>> [TOKENLOG] Tokens Discarded ({totalTokens - usedTokens}):')
-        print(f'{discarded}\x1b[0m')
+        print(f'{discarded}\x1b[0m')

ldm/invoke/globals.py

@@ -54,6 +54,9 @@ Globals.full_precision = False
 # whether we should convert ckpt files into diffusers models on the fly
 Globals.ckpt_convert = False
 
+# logging tokenization everywhere
+Globals.log_tokenization = False
+
 def global_config_file()->Path:
     return Path(Globals.root, Globals.config_dir, Globals.models_file)