neuralmonkey.config package

Submodules

neuralmonkey.config.builder module

Configuration Object Builder.

This module is responsible for instantiating objects specified by the experiment configuration.

class neuralmonkey.config.builder.ClassSymbol(string: str) → None

Bases: object

Represents a class (or other callable) in configuration.

create() → typing.Any

class neuralmonkey.config.builder.ObjectRef(expression: str) → None

Bases: object

Represents a named object or its attribute in configuration.

bind(value: typing.Any)

target

neuralmonkey.config.builder.build_config(config_dicts: typing.Dict[str, typing.Any], ignore_names: typing.Set[str], warn_unused: bool = False) → typing.Dict[str, typing.Any]

Build the model from the configuration.

Parameters:

• config_dicts – The parsed configuration file
• ignore_names – A set of names that should be ignored during the loading.
• warn_unused – Emit a warning if there are unused sections.

neuralmonkey.config.builder.build_object(value: str, all_dicts: typing.Dict[str, typing.Any], existing_objects: typing.Dict[str, typing.Any], depth: int) → typing.Any

Build an object from config dictionary of its arguments.

Works recursively.

Parameters:

• value – Value that should be resolved (either a literal value or a config section name)
• all_dicts – Configuration dictionaries used to find configuration of unconstructed objects.
• existing_objects – Dictionary of already constructed objects.
• ignore_names – Set of names that shoud be ignored.
• depth – The current depth of recursion. Used to prevent an infinite
• recursion. –

neuralmonkey.config.builder.instantiate_class(name: str, all_dicts: typing.Dict[str, typing.Any], existing_objects: typing.Dict[str, typing.Any], depth: int) → typing.Any

Instantiate a class from the configuration.

Arguments: see help(build_object)

neuralmonkey.config.configuration module

class neuralmonkey.config.configuration.Configuration

Bases: object

Configuration loader.

Loads the configuration file in an analogical way the python’s argparse.ArgumentParser works.

add_argument(name: str, required: bool = False, default: typing.Any = None, cond: typing.Callable[[typing.Any], bool] = None) → None

build_model(warn_unused=False) → None

ignore_argument(name: str) → None

load_file(path: str, changes: typing.Union[typing.List[str], NoneType] = None) → None

make_namespace(d_obj) → argparse.Namespace

save_file(path: str) → None

neuralmonkey.config.exceptions module

Module that contains exceptions handled in config parsing and loading.

exception neuralmonkey.config.exceptions.ConfigBuildException(object_name: str, original_exception: Exception) → None

Bases: Exception

Exception caused by error in loading the model.

exception neuralmonkey.config.exceptions.ConfigInvalidValueException(value: typing.Any, message: str) → None

Bases: Exception

exception neuralmonkey.config.exceptions.IniError(line: int, message: str, original_exc: typing.Union[Exception, NoneType] = None) → None

Bases: Exception

Exception caused by error in INI file syntax.

neuralmonkey.config.parsing module

Module responsible for INI parsing.

neuralmonkey.config.parsing.parse_file(config_file: typing.Iterable[str], changes: typing.Union[typing.Iterable[str], NoneType] = None) → typing.Tuple[typing.Dict[str, typing.Any], typing.Dict[str, typing.Any]]

Parse an INI file and creates all values.

neuralmonkey.config.parsing.write_file(config_dict: typing.Dict[str, typing.Any], config_file: typing.IO[str]) → None

neuralmonkey.config.utils module

Utilities.

This module contains helper functions that are suppoosed to be called from the configuration file because calling the functions or the class constructors directly would be inconvinent or impossible.

neuralmonkey.config.utils.adadelta_optimizer(**kwargs) → tensorflow.python.training.adadelta.AdadeltaOptimizer

neuralmonkey.config.utils.adam_optimizer(learning_rate: float = 0.0001) → tensorflow.python.training.adam.AdamOptimizer

neuralmonkey.config.utils.deprecated(func: typing.Callable[..., T]) → typing.Callable[..., T]

neuralmonkey.config.utils.variable(initial_value=0, trainable: bool = False, **kwargs) → tensorflow.python.ops.variables.Variable

Module contents