vision_unlearning.evaluator.text_to_image
Attributes
Classes
!!! abstract "Usage Documentation" |
Functions
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@param metadata: list of dictionaries with keys "file_name" and "text"; follows this schema: Follows this schema: https://huggingface.co/docs/datasets/v2.4.0/en/image_load#image-captioning |
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Adapted from The HuggingFace Inc. team. All rights reserved. |
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Module Contents
- vision_unlearning.evaluator.text_to_image.logger
- class vision_unlearning.evaluator.text_to_image.EvaluatorTextToImage(/, **data: Any)[source]
Bases:
pydantic.BaseModel- !!! abstract “Usage Documentation”
[Models](../concepts/models.md)
A base class for creating Pydantic models.
- __class_vars__
The names of the class variables defined on the model.
- __private_attributes__
Metadata about the private attributes of the model.
- __signature__
The synthesized __init__ [Signature][inspect.Signature] of the model.
- __pydantic_complete__
Whether model building is completed, or if there are still undefined fields.
- __pydantic_core_schema__
The core schema of the model.
- __pydantic_custom_init__
Whether the model has a custom __init__ function.
- __pydantic_decorators__
Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
- __pydantic_generic_metadata__
A dictionary containing metadata about generic Pydantic models. The origin and args items map to the [__origin__][genericalias.__origin__] and [__args__][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the parameter item maps to the __parameter__ attribute of generic classes.
- __pydantic_parent_namespace__
Parent namespace of the model, used for automatic rebuilding of models.
- __pydantic_post_init__
The name of the post-init method for the model, if defined.
- __pydantic_root_model__
Whether the model is a [RootModel][pydantic.root_model.RootModel].
- __pydantic_serializer__
The pydantic-core SchemaSerializer used to dump instances of the model.
- __pydantic_validator__
The pydantic-core SchemaValidator used to validate instances of the model.
- __pydantic_fields__
A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
- __pydantic_computed_fields__
A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
- __pydantic_extra__
A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.
- __pydantic_fields_set__
The names of fields explicitly set during instantiation.
- __pydantic_private__
Values of private attributes set on the model instance.
- model_config
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- pipeline_original: diffusers.StableDiffusionPipeline | None
- pipeline_learned: diffusers.StableDiffusionPipeline | None
- pipeline_unlearned: diffusers.StableDiffusionPipeline
- prompts_forget: List[str]
- prompts_retain: List[str]
- metric_clip: vision_unlearning.metrics.MetricImageTextSimilarity
- compute_runtimes: bool = True
- plot_show: bool = True
- vision_unlearning.evaluator.text_to_image.evaluate_painting_style(metadata: List[Dict[str, str]], metric_painting_style: vision_unlearning.metrics.MetricPaintingStyle, dataset_path: str, device: str) dict[source]
@param metadata: list of dictionaries with keys “file_name” and “text”; follows this schema: Follows this schema: https://huggingface.co/docs/datasets/v2.4.0/en/image_load#image-captioning @return metrics (as float, not yet as EvalResult) Compute metrics from already generated images
- vision_unlearning.evaluator.text_to_image.log_validation(pipeline, accelerator, epoch, num_validation_images, validation_prompt, seed, is_final_validation=False) Dict[str, PIL.Image.Image][source]
Adapted from The HuggingFace Inc. team. All rights reserved. Licensed under the Apache License, Version 2.0. Source: https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora.py