def finalize(self) -> MetricResults: # noqa: D102
hits = next(self.losses_iter)
return RankBasedMetricResults(
mean_rank={
side: {
rank_type: 10
for rank_type in RANK_TYPES
}
for side in SIDES
},
mean_reciprocal_rank={
side: {
rank_type: 1.0
for rank_type in RANK_TYPES
}
for side in SIDES
},
adjusted_mean_rank={
side: 1.0
for side in SIDES
},
hits_at_k={
side: {
rank_type: {
10: hits,
} for rank_type in RANK_TYPES
}
for side in SIDES
},
)
def finalize(self) -> MetricResults: # noqa: D102
return RankBasedMetricResults(
mean_rank=self.counter,
mean_reciprocal_rank=None,
adjusted_mean_rank=None,
hits_at_k=dict(),
)
def finalize(self) -> MetricResults: # noqa: D102
result = RankBasedMetricResults.create_random(self.random_state)
assert self.values_iter is not None
if self.key not in result.data:
raise KeyError(self.key)
result.data[self.key] = next(self.values_iter)
return result
def finalize(self) -> MetricResults: # noqa: D102
return RankBasedMetricResults(
mean_rank=None,
mean_reciprocal_rank=None,
adjusted_mean_rank=None,
hits_at_k={
RANK_AVERAGE: {
10: next(self.losses_iter),
},
},
)
def finalize(self) -> MetricResults: # noqa: D102
return RankBasedMetricResults(
arithmetic_mean_rank=self.counter,
geometric_mean_rank=None,
harmonic_mean_rank=None,
median_rank=None,
inverse_arithmetic_mean_rank=None,
inverse_geometric_mean_rank=None,
inverse_harmonic_mean_rank=None,
inverse_median_rank=None,
rank_std=None,
rank_var=None,
rank_mad=None,
adjusted_arithmetic_mean_rank=None,
adjusted_arithmetic_mean_rank_index=None,
hits_at_k=dict(),
)
def finalize(self) -> MetricResults: # noqa: D102
hits = next(self.losses_iter)
dummy_1 = {
side: {rank_type: 10.0
for rank_type in RANK_TYPES}
for side in SIDES
}
dummy_2 = {
side: {rank_type: 1.0
for rank_type in RANK_TYPES}
for side in SIDES
}
return RankBasedMetricResults(
arithmetic_mean_rank=dummy_1,
geometric_mean_rank=dummy_1,
harmonic_mean_rank=dummy_1,
median_rank=dummy_1,
inverse_arithmetic_mean_rank=dummy_2,
inverse_harmonic_mean_rank=dummy_2,
inverse_geometric_mean_rank=dummy_2,
inverse_median_rank=dummy_2,
adjusted_arithmetic_mean_rank=dummy_2,
adjusted_arithmetic_mean_rank_index={
side: {
RANK_REALISTIC: 0.0,
}
for side in SIDES
},
rank_count={
side: {rank_type: 1
for rank_type in RANK_TYPES}
for side in SIDES
},
rank_std=dummy_1,
rank_var=dummy_1,
rank_mad=dummy_1,
hits_at_k={
side: {rank_type: {
10: hits,
}
for rank_type in RANK_TYPES}
for side in SIDES
},
)
def _pre_instantiation_hook(
self, kwargs: MutableMapping[str,
Any]) -> MutableMapping[str, Any]:
kwargs = super()._pre_instantiation_hook(kwargs=kwargs)
kwargs["data"] = RankBasedMetricResults.create_random().data
return kwargs