Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

enable .and() syntax and long prompts

Browse Source
This commit is contained in:
Damian Stewart 2023-07-30 14:20:59 +02:00
parent ac22652686
commit d2c55dc011
1 changed files with 5 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
invokeai/app/invocations/compel.py
View File

@ -127,16 +127,15 @@ class CompelInvocation(BaseInvocation):
text_encoder=text_encoder,
textual_inversion_manager=ti_manager,
dtype_for_device_getter=torch_dtype,
truncate_long_prompts=True,
truncate_long_prompts=False,
)
conjunction = Compel.parse_prompt_string(self.prompt)
prompt: Union[FlattenedPrompt, Blend] = conjunction.prompts[0]
if context.services.configuration.log_tokenization:
log_tokenization_for_prompt_object(prompt, tokenizer)
log_tokenization_for_prompt_object(conjunction, tokenizer)
c, options = compel.build_conditioning_tensor_for_prompt_object(prompt)
c, options = compel.build_conditioning_tensor_for_conjunction(conjunction)
ec = InvokeAIDiffuserComponent.ExtraConditioningInfo(
tokens_count_including_eos_bos=get_max_token_count(tokenizer, conjunction),
@ -289,7 +288,7 @@ class SDXLPromptInvocationBase:
text_encoder=text_encoder,
textual_inversion_manager=ti_manager,
dtype_for_device_getter=torch_dtype,
truncate_long_prompts=True, # TODO:
truncate_long_prompts=False, # TODO:
returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED, # TODO: clip skip
requires_pooled=True,
)
@ -298,8 +297,7 @@ class SDXLPromptInvocationBase:
if context.services.configuration.log_tokenization:
# TODO: better logging for and syntax
for prompt_obj in conjunction.prompts:
log_tokenization_for_prompt_object(prompt_obj, tokenizer)
log_tokenization_for_conjunction(conjunction, tokenizer)
# TODO: ask for optimizations? to not run text_encoder twice
c, options = compel.build_conditioning_tensor_for_conjunction(conjunction)