neuralmonkey.runners.regression_runner module

class neuralmonkey.runners.regression_runner.RegressionRunExecutable(all_coders: Set[neuralmonkey.model.model_part.ModelPart], fetches: Dict[str, tensorflow.python.framework.ops.Tensor], postprocess: Union[Callable[[List[float]], List[float]], NoneType]) → None

Bases: neuralmonkey.runners.base_runner.Executable

__init__(all_coders: Set[neuralmonkey.model.model_part.ModelPart], fetches: Dict[str, tensorflow.python.framework.ops.Tensor], postprocess: Union[Callable[[List[float]], List[float]], NoneType]) → None

Initialize self. See help(type(self)) for accurate signature.

collect_results(results: List[Dict]) → None

next_to_execute() → Tuple[Set[neuralmonkey.model.model_part.ModelPart], Union[Dict, List], List[Dict[tensorflow.python.framework.ops.Tensor, Union[int, float, numpy.ndarray]]]]

Get the feedables and tensors to run.

class neuralmonkey.runners.regression_runner.RegressionRunner(output_series: str, decoder: neuralmonkey.decoders.sequence_regressor.SequenceRegressor, postprocess: Callable[[List[float]], List[float]] = None) → None

Bases: neuralmonkey.runners.base_runner.BaseRunner

A runnner that takes the predictions of a sequence regressor.

__init__(output_series: str, decoder: neuralmonkey.decoders.sequence_regressor.SequenceRegressor, postprocess: Callable[[List[float]], List[float]] = None) → None

Initialize self. See help(type(self)) for accurate signature.

get_executable(compute_losses: bool, summaries: bool, num_sessions: int) → neuralmonkey.runners.base_runner.Executable

loss_names