czbenchmarks.tasks.embedding

Attributes

logger

Classes

EmbeddingTaskInput	Pydantic model for EmbeddingTask inputs.
EmbeddingOutput	Output for embedding task.
EmbeddingTask	Task for evaluating cell representation quality using labeled data.

Module Contents

czbenchmarks.tasks.embedding.logger

class czbenchmarks.tasks.embedding.EmbeddingTaskInput(/, **data: Any)

Bases: czbenchmarks.tasks.task.TaskInput

Pydantic model for EmbeddingTask inputs.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

input_labels: czbenchmarks.types.ListLike

class czbenchmarks.tasks.embedding.EmbeddingOutput(/, **data: Any)

Bases: czbenchmarks.tasks.task.TaskOutput

Output for embedding task.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

cell_representation: czbenchmarks.tasks.types.CellRepresentation

class czbenchmarks.tasks.embedding.EmbeddingTask(*, random_seed: int = RANDOM_SEED)

Bases: czbenchmarks.tasks.task.Task

Task for evaluating cell representation quality using labeled data.

This task computes quality metrics for cell representations using ground truth labels. Currently supports silhouette score evaluation.

Parameters:

random_seed (int) – Random seed for reproducibility

display_name = 'Embedding'

description = 'Evaluate cell representation quality using silhouette score with ground truth labels.'

input_model