gluonts.core.component module#

class gluonts.core.component.BaseValidatedInitializerModel[source]#

Bases: BaseModel

Base Pydantic model for components with validated() initializers.

See also

equals_default_impl: Default semantics of a structural equality check between two objects of arbitrary type.
equals_representable_block: Specialization for Gluon HybridBlock input arguments.
equals_parameter_dict: Specialization for Gluon ParameterDict input arguments.

gluonts.core.component.equals_default_impl(this: Any, that: Any) → bool[source]#

Default semantics of a structural equality check between two objects of arbitrary type.

Two objects this and that are defined to be structurally equal if and only if the following criteria are satisfied:

Their types match.
If their initializer are validated(), their initializer arguments are pairwise structurally equal.
If their initializer are not validated(), they are referentially equal (i.e. this == that).

Parameters

this – Objects to compare.
that – Objects to compare.

Returns

A boolean value indicating whether this and that are structurally equal.

Return type

bool

gluonts.core.component.equals_dict(this: dict, that: dict) → bool[source]#

gluonts.core.component.equals_list(this: list, that: list) → bool[source]#

gluonts.core.component.equals_ndarray(this: ndarray, that: ndarray) → bool[source]#

gluonts.core.component.from_hyperparameters(cls: Type[A], **hyperparameters) → A[source]#

Reflectively create an instance of a class with a validated() initializer.

Parameters

cls – The type A of the component to be instantiated.
hyperparameters – A dictionary of key-value pairs to be used as parameters to the component initializer.

Returns

An instance of the given class.

Return type

Raises

GluonTSHyperparametersError – Wraps a ValidationError thrown when validating the initializer parameters.

gluonts.core.component.skip_encoding(v: Any) → bool[source]#

gluonts.core.component.skip_encoding(v: ParameterDict) → bool

Tells whether the input value v should be encoded using the encode() function.

This is used by validated() to determine which values need to be skipped when recording the initializer arguments for later serialization.

This is the fallback implementation, and can be specialized for specific types by registering handler functions.

gluonts.core.component.tensor_to_numpy(tensor) → ndarray[source]#
gluonts.core.component.tensor_to_numpy(tensor: ndarray) → ndarray
gluonts.core.component.tensor_to_numpy(tensor: Tensor) → ndarray
gluonts.core.component.tensor_to_numpy(tensor: NDArray) → ndarray

gluonts.core.component.validated(base_model=None)[source]#

Decorates an __init__ method with typed parameters with validation and auto-conversion logic.

>>> class ComplexNumber:
...     @validated()
...     def __init__(self, x: float = 0.0, y: float = 0.0) -> None:
...         self.x = x
...         self.y = y

Classes with decorated initializers can be instantiated using arguments of another type (e.g. an y argument of type str ). The decorator handles the type conversion logic.

>>> c = ComplexNumber(y='42')
>>> (c.x, c.y)
(0.0, 42.0)

If the bound argument cannot be converted, the decorator throws an error.

>>> c = ComplexNumber(y=None)
Traceback (most recent call last):
    ...
pydantic.v1.error_wrappers.ValidationError: 1 validation error for
ComplexNumberModel
y
  none is not an allowed value (type=type_error.none.not_allowed)

Internally, the decorator delegates all validation and conversion logic to a Pydantic model, which can be accessed through the Model attribute of the decorated initializer.

>>> ComplexNumber.__init__.Model
<class 'pydantic.v1.main.ComplexNumberModel'>

The Pydantic model is synthesized automatically from on the parameter names and types of the decorated initializer. In the ComplexNumber example, the synthesized Pydantic model corresponds to the following definition.

>>> class ComplexNumberModel(BaseValidatedInitializerModel):
...     x: float = 0.0
...     y: float = 0.0

Clients can optionally customize the base class of the synthesized Pydantic model using the base_model decorator parameter. The default behavior uses BaseValidatedInitializerModel and its model config.