Guiders

Classifier-free guidance steers model generation that better match a prompt and is commonly used to improve generation quality, control, and adherence to prompts. There are different types of guidance methods, and in Diffusers, they are known as guiders. Like blocks, it is easy to switch and use different guiders for different use cases without rewriting the pipeline.

This guide will show you how to switch guiders, adjust guider parameters, and load and share them to the Hub.

Switching guiders

[ClassifierFreeGuidance] is the default guider and created when a pipeline is initialized with init_pipeline. It is created by from_config which means it doesn't require loading specifications from a modular repository. A guider won't be listed in modular_model_index.json.

Use get_component_spec to inspect a guider.

t2i_pipeline.get_component_spec("guider")
ComponentSpec(name='guider', type_hint=<class 'diffusers.guiders.classifier_free_guidance.ClassifierFreeGuidance'>, description=None, config=FrozenDict([('guidance_scale', 7.5), ('guidance_rescale', 0.0), ('use_original_formulation', False), ('start', 0.0), ('stop', 1.0), ('_use_default_values', ['start', 'guidance_rescale', 'stop', 'use_original_formulation'])]), repo=None, subfolder=None, variant=None, revision=None, default_creation_method='from_config')

Switch to a different guider by passing the new guider to update_components.

Tip

Changing guiders will return text letting you know you're changing the guider type.

ModularPipeline.update_components: adding guider with new type: PerturbedAttentionGuidance, previous type: ClassifierFreeGuidance

from mindone.diffusers import LayerSkipConfig, PerturbedAttentionGuidance

config = LayerSkipConfig(indices=[2, 9], fqn="mid_block.attentions.0.transformer_blocks", skip_attention=False, skip_attention_scores=True, skip_ff=False)
guider = PerturbedAttentionGuidance(
    guidance_scale=5.0, perturbed_guidance_scale=2.5, perturbed_guidance_config=config
)
t2i_pipeline.update_components(guider=guider)

Use get_component_spec again to verify the guider type is different.

t2i_pipeline.get_component_spec("guider")
ComponentSpec(name='guider', type_hint=<class 'mindone.diffusers.guiders.perturbed_attention_guidance.PerturbedAttentionGuidance'>, description=None, config=FrozenDict([('guidance_scale', 5.0), ('perturbed_guidance_scale', 2.5), ('perturbed_guidance_start', 0.01), ('perturbed_guidance_stop', 0.2), ('perturbed_guidance_layers', None), ('perturbed_guidance_config', LayerSkipConfig(indices=[2, 9], fqn='mid_block.attentions.0.transformer_blocks', skip_attention=False, skip_attention_scores=True, skip_ff=False, dropout=1.0)), ('guidance_rescale', 0.0), ('use_original_formulation', False), ('start', 0.0), ('stop', 1.0), ('_use_default_values', ['perturbed_guidance_start', 'use_original_formulation', 'perturbed_guidance_layers', 'stop', 'start', 'guidance_rescale', 'perturbed_guidance_stop']), ('_class_name', 'PerturbedAttentionGuidance'), ('_diffusers_version', '0.35.0.dev0')]), repo=None, subfolder=None, variant=None, revision=None, default_creation_method='from_config')

Loading custom guiders

Guiders that are already saved on the Hub with a modular_model_index.json file are considered a from_pretrained component now instead of a from_config component.

{
  "guider": [
    null,
    null,
    {
      "repo": "YiYiXu/modular-loader-t2i-guider",
      "revision": null,
      "subfolder": "pag_guider",
      "type_hint": [
        "mindone.diffusers",
        "PerturbedAttentionGuidance"
      ],
      "variant": null
    }
  ]
}

The guider is only created after calling load_default_components based on the loading specification in modular_model_index.json.

t2i_pipeline = t2i_blocks.init_pipeline("YiYiXu/modular-doc-guider")
# not created during init
assert t2i_pipeline.guider is None
t2i_pipeline.load_default_components()
# loaded as PAG guider
t2i_pipeline.guider

Changing guider parameters

The guider parameters can be adjusted with either the create method or with update_components. The example below changes the guidance_scale value.

guider_spec = t2i_pipeline.get_component_spec("guider")
guider = guider_spec.create(guidance_scale=10)
t2i_pipeline.update_components(guider=guider)

guider_spec = t2i_pipeline.get_component_spec("guider")
guider_spec.config["guidance_scale"] = 10
t2i_pipeline.update_components(guider=guider_spec)

Uploading custom guiders

Call the [~utils.PushToHubMixin.push_to_hub] method on a custom guider to share it to the Hub.

guider.push_to_hub("YiYiXu/modular-loader-t2i-guider", subfolder="pag_guider")

To make this guider available to the pipeline, either modify the modular_model_index.json file or use the update_components method.

Edit the modular_model_index.json file and add a loading specification for the guider by pointing to a folder containing the guider config.

{
  "guider": [
    "mindone.diffusers",
    "PerturbedAttentionGuidance",
    {
      "repo": "YiYiXu/modular-loader-t2i-guider",
      "revision": null,
      "subfolder": "pag_guider",
      "type_hint": [
        "mindone.diffusers",
        "PerturbedAttentionGuidance"
      ],
      "variant": null
    }
  ],

Change the default_creation_method to from_pretrained and use update_components to update the guider and component specifications as well as the pipeline config.

Tip

Changing the creation method will return text letting you know you're changing the creation type to from_pretrained.

ModularPipeline.update_components: changing the default_creation_method of guider from from_config to from_pretrained.

guider_spec = t2i_pipeline.get_component_spec("guider")
guider_spec.default_creation_method="from_pretrained"
guider_spec.repo="YiYiXu/modular-loader-t2i-guider"
guider_spec.subfolder="pag_guider"
pag_guider = guider_spec.load()
t2i_pipeline.update_components(guider=pag_guider)

To make it the default guider for a pipeline, call push_to_hub. This is an optional step and not necessary if you are only experimenting locally.

t2i_pipeline.push_to_hub("YiYiXu/modular-doc-guider")