caikit.runtime.model_management.loaded_model

A LoadedModel is a metadata wrapper around an instance of a core.ModuleBase class that contains the additional information needed to manage that model in the runtime.

Attributes

log

error

CaikitModelFuture

CaikitModelFutureFactory

Classes

LoadedModel

Module Contents

caikit.runtime.model_management.loaded_model.log[source]
caikit.runtime.model_management.loaded_model.error
caikit.runtime.model_management.loaded_model.CaikitModelFuture
caikit.runtime.model_management.loaded_model.CaikitModelFutureFactory
class caikit.runtime.model_management.loaded_model.LoadedModel[source]
__doc__ = Multiline-String
Show Value
"""
A LoadedModel is a metadata wrapper around an instance of a core.ModuleBase
class that contains the additional information needed to manage that model in
the runtime.
"""
class Builder[source]

The LoadedModel.Builder allows the LoadedModel instance to be constructed in pieces with chained ‘.’ getattr semantics.

_model_to_build
model_future_factory(caikit_model_future_factory: CaikitModelFutureFactory) LoadedModel[source]
fail_callback(callback: Callable) LoadedModel[source]
path(model_path: str) LoadedModel[source]
type(model_type: str) LoadedModel[source]
id(model_id: str) LoadedModel[source]
retries(retries: int) LoadedModel[source]
build() LoadedModel[source]
_caikit_model_future_factory: CaikitModelFutureFactory | None = None
_caikit_model_future: CaikitModelFuture | None = None
_model: caikit.core.ModuleBase | None = None
_fail_callback: Callable | None = None
_model_id: str = ''
_model_path: str = ''
_model_type: str = ''
_retries: int = 0
_size: int | None = None
id() str[source]
model() caikit.core.ModuleBase[source]
loading() bool[source]

Return if a model load job has completed. The model job might have failed

Returns:

bool: If a local model job is still running

loaded() bool[source]

Return if a model load job has resulted in a local instance

Returns:

bool: If a local model instance is available

wait()[source]
type() str[source]
path() str[source]
size() int[source]
has_size() bool[source]
set_size(model_size: int)[source]