kd.metrics.Accuracy#

class kauldron.metrics.Accuracy( *, logits: typing.Annotated[typing.Any, <object object at 0x76412092fb90>] = '__KEY_REQUIRED__', labels: typing.Annotated[typing.Any, <object object at 0x76412092fb90>] = '__KEY_REQUIRED__', mask: typing.Annotated[typing.Any, <object object at 0x76412092fb90>] | None = None, )[source]

Bases: kauldron.metrics.base.Metric

Classification Accuracy.

logits: Annotated[Any, <object object at 0x76412092fb90>] = '__KEY_REQUIRED__'

labels: Annotated[Any, <object object at 0x76412092fb90>] = '__KEY_REQUIRED__'

mask: Annotated[Any, <object object at 0x76412092fb90>] | None = None

class State( total: "Float['']", count: "Float['']", *, parent: '_MetricT' = <_EMPTY_TYPE.EMPTY: 1>, )[source]

Bases: kauldron.metrics.base_state.AverageState

merge( other: kauldron.metrics.base_state.AverageState, ) → kauldron.metrics.base_state.AverageState[source]

Returns a new state that is the accumulation of self and other.

Parameters:: other – A State whose intermediate values should be accumulated onto the values of self.
Returns:: A new State that accumulates the value from both self and other.

replace(**updates): Returns a new object replacing the specified fields with new values.

get_state( logits: jaxtyping.Float[Array, '*b n'] | jaxtyping.Float[ndarray, '*b n'], labels: jaxtyping.Int[Array, '*b 1'] | jaxtyping.Int[ndarray, '*b 1'], mask: jaxtyping.Bool[Array, '*b 1'] | jaxtyping.Bool[ndarray, '*b 1'] | jaxtyping.Float[Array, '*b 1'] | jaxtyping.Float[ndarray, '*b 1'] | None = None, ) → kauldron.metrics.classification.Accuracy.State[source]

empty() → kauldron.metrics.base.Metric.State[source]