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Prompt cache support for Flux

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Disty0
2024-08-12 01:02:13 +03:00
parent da9c46c628
commit 70c2e84d26
3 changed files with 21 additions and 6 deletions
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modules/prompt_parser_diffusers.py
+12 -3
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@@ -147,7 +147,12 @@ def get_tokens(msg, prompt):
def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, clip_skip: typing.Optional[int] = None):
if 'StableDiffusion' not in pipe.__class__.__name__ and 'DemoFusion' not in pipe.__class__.__name__ and 'StableCascade' not in pipe.__class__.__name__:
if (
'StableDiffusion' not in pipe.__class__.__name__ and
'DemoFusion' not in pipe.__class__.__name__ and
'StableCascade' not in pipe.__class__.__name__ and
'Flux' not in pipe.__class__.__name__
):
shared.log.warning(f"Prompt parser not supported: {pipe.__class__.__name__}")
return
elif shared.opts.sd_textencoder_cache and prompts == cache.get('prompts', None) and negative_prompts == cache.get('negative_prompts', None) and clip_skip == cache.get('clip_skip', None) and cache.get('model_type', None) == shared.sd_model_type and steps == cache.get('steps', None):
@@ -168,7 +173,7 @@ def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, c
p.negative_embeds = []
p.negative_pooleds = []
if shared.opts.diffusers_offload_mode in {"balanced", "cpu"} and hasattr(pipe, "_all_hooks") and hasattr(pipe, "maybe_free_model_hooks"):
if hasattr(pipe, "maybe_free_model_hooks"):
# if the last job is interrupted, model will stay in the vram and cause oom, send everything back to cpu before continuing
pipe.maybe_free_model_hooks()
devices.torch_gc()
@@ -204,7 +209,7 @@ def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, c
if debug_enabled:
get_tokens('positive', prompts[0])
get_tokens('negative', negative_prompts[0])
if shared.opts.diffusers_offload_mode in {"balanced", "cpu"} and hasattr(pipe, "_all_hooks") and hasattr(pipe, "maybe_free_model_hooks"):
if hasattr(pipe, "maybe_free_model_hooks"):
# text encoder will stay in the vram and cause oom, send everything back to cpu before continuing
pipe.maybe_free_model_hooks()
debug(f"Prompt encode: time={(time.time() - t0):.3f}")
@@ -332,6 +337,10 @@ def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", c
negatives.pop(0)
negative_weights.pop(0)
if "Flux" in pipe.__class__.__name__: # clip is only used for the pooled embeds
prompt_embeds, pooled_prompt_embeds, _ = pipe.encode_prompt(prompt=prompt, prompt_2=prompt_2, device=device, num_images_per_prompt=1)
return prompt_embeds, pooled_prompt_embeds, None, None # no negative support
embedding_providers = prepare_embedding_providers(pipe, clip_skip)
empty_embedding_providers = None
if 'StableCascade' in pipe.__class__.__name__: