




'''simple docstring'''







import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
   from cookiecutter.main import cookiecutter

   A     =True
except ImportError:
   A     =False

A     =logging.get_logger(__name__)  # pylint: disable=invalid-name





def 						snake_case_							(_a	:							Namespace     ):
    return AddNewModelCommand(args.testing    ,   args.testing_file    ,   path=args.path     )







class 			_a  (	__a ):
       @staticmethod
       def     A      (	lowercase						:	ArgumentParser				):



           '''simple docstring'''

           UpperCAmelCase			       =		parser.add_parser('''add-new-model'''				)
           add_new_model_parser.add_argument('''--testing'''   ,				action='''store_true'''   ,				help='''If in testing mode.'''				)
           add_new_model_parser.add_argument('''--testing_file'''   ,				type=lowercase   ,				help='''Configuration file on which to run.'''				)
           add_new_model_parser.add_argument(
               '''--path'''   ,				type=lowercase   ,				help='''Path to cookiecutter. Should only be used for testing purposes.'''				)
           add_new_model_parser.set_defaults(func=lowercase				)
       def __init__(	self						:	List[Any]   ,				lowercase						:	bool   ,				lowercase						:	str   ,				lowercase						:	Dict=None   ,				*lowercase						:	Optional[Any]				):



           '''simple docstring'''

           UpperCAmelCase			       =		testing
           UpperCAmelCase			       =		testing_file
           UpperCAmelCase			       =		path







       def     A      (	self						:	Optional[Any]				):



           '''simple docstring'''

           warnings.warn(
               '''The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. '''
               '''It is not actively maintained anymore, so might give a result that won\'t pass all tests and quality '''
               '''checks, you should use `transformers-cli add-new-model-like` instead.'''				)
           if not _has_cookiecutter:
               raise ImportError(
                   '''Model creation dependencies are required to use the `add_new_model` command. Install them by running '''
                   '''the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n'''				)
           # Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
           UpperCAmelCase			       =		[directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:22]]
           if len(lowercase				) > 0:
               raise ValueError(
                   '''Several directories starting with `cookiecutter-template-` in current working directory. '''
                   '''Please clean your directory by removing all folders starting with `cookiecutter-template-` or '''
                   '''change your working directory.'''				)

           UpperCAmelCase			       =		(
               Path(lowercase				).parent.parent.parent.parent if self._path is None else Path(self._path				).parent.parent
           )
           UpperCAmelCase			       =		path_to_transformer_root / '''templates''' / '''adding_a_new_model'''

           # Execute cookiecutter
           if not self._testing:
               cookiecutter(str(lowercase				)				)
           else:
               with open(self._testing_file   ,				'''r'''				) as configuration_file:
                   UpperCAmelCase			       =		json.load(lowercase				)

               cookiecutter(
                   str(path_to_cookiecutter if self._path is None else self._path				)   ,				no_input=lowercase   ,				extra_context=lowercase   ,				)

           UpperCAmelCase			       =		[directory for directory in os.listdir() if '''cookiecutter-template-''' in directory[:22]][0]

           # Retrieve configuration
           with open(directory + '''/configuration.json'''   ,				'''r'''				) as configuration_file:
               UpperCAmelCase			       =		json.load(lowercase				)

           UpperCAmelCase			       =		configuration['''lowercase_modelname''']
           UpperCAmelCase			       =		configuration['''generate_tensorflow_pytorch_and_flax''']
           os.remove(f"{directory}/configuration.json"				)

           UpperCAmelCase			       =		'''PyTorch''' in generate_tensorflow_pytorch_and_flax
           UpperCAmelCase			       =		'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
           UpperCAmelCase			       =		'''Flax''' in generate_tensorflow_pytorch_and_flax

           UpperCAmelCase			       =		f"{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}"
           os.makedirs(lowercase   ,				exist_ok=lowercase				)
           os.makedirs(f"{path_to_transformer_root}/tests/models/{lowercase_model_name}"   ,				exist_ok=lowercase				)

           # Tests require submodules as they have parent imports
           with open(f"{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py"   ,				'''w'''				):
               pass

           shutil.move(
               f"{directory}/__init__.py"   ,				f"{model_dir}/__init__.py"   ,				)
           shutil.move(
               f"{directory}/configuration_{lowercase_model_name}.py"   ,				f"{model_dir}/configuration_{lowercase_model_name}.py"   ,				)

           def remove_copy_lines(lowercase						:	Union[str, Any]				):
               with open(lowercase   ,				'''r'''				) as f:
                   UpperCAmelCase			       =		f.readlines()
               with open(lowercase   ,				'''w'''				) as f:
                   for line in lines:
                       if "# Copied from transformers." not in line:
                           f.write(lowercase				)

           if output_pytorch:
               if not self._testing:
                   remove_copy_lines(f"{directory}/modeling_{lowercase_model_name}.py"				)

               shutil.move(
                   f"{directory}/modeling_{lowercase_model_name}.py"   ,				f"{model_dir}/modeling_{lowercase_model_name}.py"   ,				)

               shutil.move(
                   f"{directory}/test_modeling_{lowercase_model_name}.py"   ,				f"{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py"   ,				)
           else:
               os.remove(f"{directory}/modeling_{lowercase_model_name}.py"				)
               os.remove(f"{directory}/test_modeling_{lowercase_model_name}.py"				)

           if output_tensorflow:
               if not self._testing:
                   remove_copy_lines(f"{directory}/modeling_tf_{lowercase_model_name}.py"				)

               shutil.move(
                   f"{directory}/modeling_tf_{lowercase_model_name}.py"   ,				f"{model_dir}/modeling_tf_{lowercase_model_name}.py"   ,				)

               shutil.move(
                   f"{directory}/test_modeling_tf_{lowercase_model_name}.py"   ,				f"{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py"   ,				)
           else:
               os.remove(f"{directory}/modeling_tf_{lowercase_model_name}.py"				)
               os.remove(f"{directory}/test_modeling_tf_{lowercase_model_name}.py"				)

           if output_flax:
               if not self._testing:
                   remove_copy_lines(f"{directory}/modeling_flax_{lowercase_model_name}.py"				)

               shutil.move(
                   f"{directory}/modeling_flax_{lowercase_model_name}.py"   ,				f"{model_dir}/modeling_flax_{lowercase_model_name}.py"   ,				)

               shutil.move(
                   f"{directory}/test_modeling_flax_{lowercase_model_name}.py"   ,				f"{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py"   ,				)
           else:
               os.remove(f"{directory}/modeling_flax_{lowercase_model_name}.py"				)
               os.remove(f"{directory}/test_modeling_flax_{lowercase_model_name}.py"				)

           shutil.move(
               f"{directory}/{lowercase_model_name}.md"   ,				f"{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md"   ,				)

           shutil.move(
               f"{directory}/tokenization_{lowercase_model_name}.py"   ,				f"{model_dir}/tokenization_{lowercase_model_name}.py"   ,				)

           shutil.move(
               f"{directory}/tokenization_fast_{lowercase_model_name}.py"   ,				f"{model_dir}/tokenization_{lowercase_model_name}_fast.py"   ,				)

           from os import fdopen, remove
           from shutil import copymode, move
           from tempfile import mkstemp

           def replace(lowercase						:	str   ,				lowercase						:	str   ,				lowercase						:	List[str]				):
               # Create temp file
               UpperCAmelCase       ,     UpperCAmelCase			       =		mkstemp()
               UpperCAmelCase			       =		False
               with fdopen(lowercase   ,				'''w'''				) as new_file:
                   with open(lowercase				) as old_file:
                       for line in old_file:
                           new_file.write(lowercase				)
                           if line_to_copy_below in line:
                               UpperCAmelCase			       =		True
                               for line_to_copy in lines_to_copy:
                                   new_file.write(lowercase				)

               if not line_found:
                   raise ValueError(f"Line {line_to_copy_below} was not found in file."				)

               # Copy the file permissions from the old file to the new file
               copymode(lowercase   ,				lowercase				)
               # Remove original file
               remove(lowercase				)
               # Move new file
               move(lowercase   ,				lowercase				)

           def skip_units(lowercase						:	List[Any]				):
               return (
                   ("generating PyTorch" in line and not output_pytorch)
                   or ("generating TensorFlow" in line and not output_tensorflow)
                   or ("generating Flax" in line and not output_flax)
               )

           def replace_in_files(lowercase						:	Tuple				):
               with open(lowercase				) as datafile:
                   UpperCAmelCase			       =		[]
                   UpperCAmelCase			       =		False
                   UpperCAmelCase			       =		False
                   for line in datafile:
                       if "# To replace in: " in line and "##" not in line:
                           UpperCAmelCase			       =		line.split('''"'''				)[1]
                           UpperCAmelCase			       =		skip_units(lowercase				)
                       elif "# Below: " in line and "##" not in line:
                           UpperCAmelCase			       =		line.split('''"'''				)[1]
                           UpperCAmelCase			       =		skip_units(lowercase				)
                       elif "# End." in line and "##" not in line:
                           if not skip_file and not skip_snippet:
                               replace(lowercase   ,				lowercase   ,				lowercase				)

                           UpperCAmelCase			       =		[]
                       elif "# Replace with" in line and "##" not in line:
                           UpperCAmelCase			       =		[]
                       elif "##" not in line:
                           lines_to_copy.append(lowercase				)

               remove(lowercase				)

           replace_in_files(f"{directory}/to_replace_{lowercase_model_name}.py"				)
           os.rmdir(lowercase				)










'''simple docstring'''







from queue import PriorityQueue
from typing import Any

import numpy as np





def 						snake_case_							(_a	:							dict    ,   _a	:							str    ,   _a	:							set    ,   _a	:							set    ,   _a	:							dict    ,   _a	:							dict    ,   _a	:							PriorityQueue    ,   _a	:							dict    ,   _a	:							float | int    ,   ):
    for nxt, d in graph[v]:
        if nxt in visited_forward:
            continue
        UpperCAmelCase			       =		cst_fwd.get(_a    ,   np.inf     )
        UpperCAmelCase			       =		cst_fwd[v] + d
        if new_cost_f < old_cost_f:
            queue.put((new_cost_f, nxt)     )
            UpperCAmelCase			       =		new_cost_f
            UpperCAmelCase			       =		v
        if nxt in visited_backward:
            if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
                UpperCAmelCase			       =		cst_fwd[v] + d + cst_bwd[nxt]
    return shortest_distance





def 						snake_case_							(_a	:							str    ,   _a	:							str    ,   _a	:							dict    ,   _a	:							dict     ):
    UpperCAmelCase			       =		-1

    UpperCAmelCase			       =		set()
    UpperCAmelCase			       =		set()
    UpperCAmelCase			       =		{source: 0}
    UpperCAmelCase			       =		{destination: 0}
    UpperCAmelCase			       =		{source: None}
    UpperCAmelCase			       =		{destination: None}
    UpperCAmelCase			       =		PriorityQueue()
    UpperCAmelCase			       =		PriorityQueue()

    UpperCAmelCase			       =		np.inf

    queue_forward.put((0, source)     )
    queue_backward.put((0, destination)     )

    if source == destination:
        return 0

    while not queue_forward.empty() and not queue_backward.empty():
        UpperCAmelCase       ,     UpperCAmelCase			       =		queue_forward.get()
        visited_forward.add(_a     )

        UpperCAmelCase       ,     UpperCAmelCase			       =		queue_backward.get()
        visited_backward.add(_a     )

        UpperCAmelCase			       =		pass_and_relaxation(
            _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   )

        UpperCAmelCase			       =		pass_and_relaxation(
            _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   _a    ,   )

        if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
            break

    if shortest_distance != np.inf:
        UpperCAmelCase			       =		shortest_distance
    return shortest_path_distance


A     ={
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
A     ={
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
   import doctest

   doctest.testmod()




