neuralmonkey.runners.base_runner module

class neuralmonkey.runners.base_runner.BaseRunner(output_series: str, decoder: MP) → None

Bases: typing.Generic

__init__(output_series: str, decoder: MP) → None

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

decoder_data_id

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

loss_names

class neuralmonkey.runners.base_runner.Executable

Bases: object

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]]]]

class neuralmonkey.runners.base_runner.ExecutionResult

Bases: neuralmonkey.runners.base_runner.ExecutionResult

A data structure that represents a result of a graph execution.

The goal of each runner is to populate this structure and set it as its self.result.

outputs

A batch of outputs of the runner.

losses

A (possibly empty) list of loss values computed during the run.

scalar_summaries

A TensorFlow summary object with scalar values.

histogram_summaries

A TensorFlow summary object with histograms.

image_summaries

A TensorFlow summary object with images.

neuralmonkey.runners.base_runner.reduce_execution_results(execution_results: List[neuralmonkey.runners.base_runner.ExecutionResult]) → neuralmonkey.runners.base_runner.ExecutionResult

Aggregate execution results into one.