neuralmonkey.runners.plain_runner module¶
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class
neuralmonkey.runners.plain_runner.
PlainExecutable
(all_coders: Set[neuralmonkey.model.model_part.ModelPart], fetches: Dict[tensorflow.python.framework.ops.Tensor, Union[int, float, numpy.ndarray]], num_sessions: int, vocabulary: neuralmonkey.vocabulary.Vocabulary, postprocess: Union[Callable[[List[List[str]]], List[List[str]]], NoneType]) → None¶ Bases:
neuralmonkey.runners.base_runner.Executable
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__init__
(all_coders: Set[neuralmonkey.model.model_part.ModelPart], fetches: Dict[tensorflow.python.framework.ops.Tensor, Union[int, float, numpy.ndarray]], num_sessions: int, vocabulary: neuralmonkey.vocabulary.Vocabulary, postprocess: Union[Callable[[List[List[str]]], List[List[str]]], NoneType]) → None¶ Initialize self. See help(type(self)) for accurate signature.
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collect_results
(results: List[Dict]) → None¶
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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.
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class
neuralmonkey.runners.plain_runner.
PlainRunner
(output_series: str, decoder: Union[neuralmonkey.decoders.autoregressive.AutoregressiveDecoder, neuralmonkey.decoders.ctc_decoder.CTCDecoder, neuralmonkey.decoders.classifier.Classifier, neuralmonkey.decoders.sequence_labeler.SequenceLabeler], postprocess: Callable[[List[List[str]]], List[List[str]]] = None) → None¶ Bases:
neuralmonkey.runners.base_runner.BaseRunner
A runner which takes the output from decoder.decoded.
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__init__
(output_series: str, decoder: Union[neuralmonkey.decoders.autoregressive.AutoregressiveDecoder, neuralmonkey.decoders.ctc_decoder.CTCDecoder, neuralmonkey.decoders.classifier.Classifier, neuralmonkey.decoders.sequence_labeler.SequenceLabeler], postprocess: Callable[[List[List[str]]], List[List[str]]] = None) → None¶ Initialize self. See help(type(self)) for accurate signature.
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get_executable
(compute_losses: bool, summaries: bool, num_sessions: int)¶
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loss_names
¶
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