Pydantic utilities¶

Functions and classes to handle the validation of hyperparameters using Pydantic.

exception metatrain.utils.pydantic.MetatrainValidationError(model: Any, errors: list[dict])[source]¶

This class transforms Pydantic validation errors into a more user-friendly format.

Parameters:

model (Any) – The Pydantic model class or TypedDict that was used for validation.
errors (list[dict]) – The list of Pydantic error dictionaries.

get_error_string(error: dict) → str[source]¶

Given an individual error from Pydantic, return a user-friendly string.

default_pydantic(err: dict) → str[source]¶

Default Pydantic error formatting.

metatrain.utils.pydantic.validate(model_cls: Any, data: dict, **kwargs: Any) → dict[source]¶

Validate with pydantic, raising custom metatrain errors.

Parameters:

model_cls (Any) – The Pydantic model class to use for validation. If it is not a pydantic model, it will be adapted to pydantic using pydantic.TypeAdapter.
data (dict) – The data to validate.
**kwargs (Any) – Additional keyword arguments to pass to the validation method.

Returns:

The validated options, which have been sanitized.

Raises:

MetatrainValidationError – If validation fails.

Return type:

dict

metatrain.utils.pydantic.validate_architecture_options(options: dict, model_hypers: type, trainer_hypers: type) → dict[source]¶

Validate architecture-specific options using Pydantic.

Parameters:

Returns:

The validated options, which have been sanitized.

Raises:

MetatrainValidationError – If validation fails.

Return type:

dict

metatrain.utils.pydantic.validate_base_options(options: dict) → dict[source]¶

Validate base options using Pydantic.

metatrain.utils.pydantic.validate_eval_options(options: dict) → dict[source]¶

Validate evaluation options using Pydantic.