dacapo.experiments.tasks.predictors.dummy_predictor
Classes
A dummy predictor class that inherits from the base Predictor class. |
Module Contents
- class dacapo.experiments.tasks.predictors.dummy_predictor.DummyPredictor(embedding_dims)
A dummy predictor class that inherits from the base Predictor class.
- embedding_dims
The number of embedding dimensions.
- Type:
int
- __init__(self, embedding_dims
int): Initializes a new instance of the DummyPredictor class.
- create_model(self, architecture)
Creates a model using the given architecture.
- create_target(self, gt)
Creates a target based on the ground truth.
- create_weight(self, gt, target, mask, moving_class_counts=None)
Creates a weight based on the ground truth, target, and mask.
- output_array_type()
Gets the output array type.
Notes
This is a subclass of Predictor.
- embedding_dims
- create_model(architecture)
Creates a model using the given architecture.
- Parameters:
architecture – The architecture to use for creating the model.
- Returns:
The created model.
- Return type:
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> model = predictor.create_model(architecture)
- create_target(gt)
Creates a target based on the ground truth.
- Parameters:
gt – The ground truth.
- Returns:
The created target.
- Return type:
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> predictor.create_target(gt)
- create_weight(gt, target, mask, moving_class_counts=None)
Creates a weight based on the ground truth, target, and mask.
- Parameters:
gt – The ground truth.
target – The target.
mask – The mask.
moving_class_counts – The moving class counts.
- Returns:
The created weight and None.
- Return type:
Tuple[NumpyArray, None]
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> predictor.create_weight(gt, target, mask, moving_class_counts)
- property output_array_type
- Gets the output array type.
- Returns:
The output array type.
- Return type:
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> predictor.output_array_type