# Path: nmt_chainer/utilities/argument_parsing_tools.py
# class OrderedNamespace(OrderedDict):
# class ParseOptionRecorder(object):
# class ParserWithNoneDefaultAndNoGroup(object):
# class ArgumentActionNotOverwriteWithNone(argparse.Action):
#     def __init__(self, *args, **kwargs):
#     def set_readonly(self):
#     def __setitem__(self, *args, **kwargs):
#     def __getattr__(self, key):
#     def save_to(self, filename):
#     def load_from(cls, filename):
#     def convert_to_ordered_namespace(cls, ordered_dict):
#     def update_recursive(self, other, valid_keys, add_absent_keys=False):
#     def pretty_print(self, indent=4, discard_section=("metadata",)):
#     def copy(self, readonly=None):
#     def add_section(self, name, keep_at_bottom=None, overwrite=False):
#     def insert_section(self, name, content, even_if_readonly=False, keep_at_bottom=None, overwrite=False):
#     def add_metadata_infos(self, version_num, overwrite=False):
#     def set_metadata_modified_time(self):
#     def __init__(self, name=None, group_title_to_section=None, ignore_positional_arguments=set()):
#     def add_argument(self, argument_name, *args, **kwargs):
#     def add_argument_group(self, title, desc=None):
#     def convert_args_to_ordered_dict(self, args, args_is_namespace=True):
#     def __init__(self):
#     def add_argument(self, *args, **kwargs):
#     def add_argument_group(self, *args, **kwargs):
#     def get_args_given(self, arglist):
#     def __call__(self, parser, namespace, values, option_string=None):


import logging
import sys
import six
    import nmt_chainer.models.rnn_cells_config
    import argparse
    import nmt_chainer.training_module.train
from nmt_chainer.utilities import argument_parsing_tools
"""train_config.py: Parse training arguments and create config dictionnary."""
from __future__ import absolute_import, division, print_function, unicode_literals



logging.basicConfig()
log = logging.getLogger("rnns:train_config")
log.setLevel(logging.INFO)

_CONFIG_SECTION_TO_DESCRIPTION = {"model": "Model Description",
                                  "training": "Training Parameters",
                                  "training_management": "Training Management and Monitoring"}


def define_parser(parser):
    parser.add_argument("data_prefix", nargs="?",

# Path: nmt_chainer/utilities/argument_parsing_tools.py
# class OrderedNamespace(OrderedDict):
# class ParseOptionRecorder(object):
# class ParserWithNoneDefaultAndNoGroup(object):
# class ArgumentActionNotOverwriteWithNone(argparse.Action):
#     def __init__(self, *args, **kwargs):
#     def set_readonly(self):
#     def __setitem__(self, *args, **kwargs):
#     def __getattr__(self, key):
#     def save_to(self, filename):
#     def load_from(cls, filename):
#     def convert_to_ordered_namespace(cls, ordered_dict):
#     def update_recursive(self, other, valid_keys, add_absent_keys=False):
#     def pretty_print(self, indent=4, discard_section=("metadata",)):
#     def copy(self, readonly=None):
#     def add_section(self, name, keep_at_bottom=None, overwrite=False):
#     def insert_section(self, name, content, even_if_readonly=False, keep_at_bottom=None, overwrite=False):
#     def add_metadata_infos(self, version_num, overwrite=False):
#     def set_metadata_modified_time(self):
#     def __init__(self, name=None, group_title_to_section=None, ignore_positional_arguments=set()):
#     def add_argument(self, argument_name, *args, **kwargs):
#     def add_argument_group(self, title, desc=None):
#     def convert_args_to_ordered_dict(self, args, args_is_namespace=True):
#     def __init__(self):
#     def add_argument(self, *args, **kwargs):
#     def add_argument_group(self, *args, **kwargs):
#     def get_args_given(self, arglist):
#     def __call__(self, parser, namespace, values, option_string=None):


# Path: nmt_chainer/training_module/train_config.py
import logging
import sys
import six
    import nmt_chainer.models.rnn_cells_config
    import argparse
    import nmt_chainer.training_module.train
from nmt_chainer.utilities import argument_parsing_tools

"""train_config.py: Parse training arguments and create config dictionnary."""
from __future__ import absolute_import, division, print_function, unicode_literals



logging.basicConfig()
log = logging.getLogger("rnns:train_config")
log.setLevel(logging.INFO)

_CONFIG_SECTION_TO_DESCRIPTION = {"model": "Model Description",
                                  "training": "Training Parameters",
                                  "training_management": "Training Management and Monitoring"}


def define_parser(parser):
    parser.add_argument("data_prefix", nargs="?",

                        action=argument_parsing_tools.ArgumentActionNotOverwriteWithNone,