

# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						List[str]	,				_SCREAMING_SNAKE_CASE   :						str    ):





    """simple docstring"""


    if name != "training_function" and name != "main":
        raise ValueError(f"""Incorrect function name passed: {name}, choose either 'main' or 'training_function'"""    )
    SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_													=  [], False
    for line in lines:
        if not found_start and f"""def {name}""" in line:
            SCREAMING_SNAKE_CASE_													=  True
            good_lines.append(_SCREAMING_SNAKE_CASE    )
            continue
        if found_start:
            if name == "training_function" and "def main" in line:
                return good_lines
            if name == "main" and "if __name__" in line:
                return good_lines
            good_lines.append(_SCREAMING_SNAKE_CASE    )


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						List[str]    ):





    """simple docstring"""


    return [line for line in lines if not line.lstrip().startswith('#'    ) and line != "\n"]





def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						str	,				_SCREAMING_SNAKE_CASE   :						str	,				_SCREAMING_SNAKE_CASE   :						bool	,				_SCREAMING_SNAKE_CASE   :						str = None    ):





    """simple docstring"""


    with open(_SCREAMING_SNAKE_CASE	,				'r'    ) as f:
        SCREAMING_SNAKE_CASE_													=  f.readlines()
    with open(os.path.abspath(os.path.join('examples'	,				'nlp_example.py'    )    )	,				'r'    ) as f:
        SCREAMING_SNAKE_CASE_													=  f.readlines()
    with open(_SCREAMING_SNAKE_CASE	,				'r'    ) as f:
        SCREAMING_SNAKE_CASE_													=  f.readlines()
    if secondary_filename is not None:
        with open(_SCREAMING_SNAKE_CASE	,				'r'    ) as f:
            SCREAMING_SNAKE_CASE_													=  f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
    if parser_only:
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'main'    )    )
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'main'    )    )
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'main'    )    )
        if secondary_filename is not None:
            SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'main'    )    )
    else:
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'training_function'    )    )
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'training_function'    )    )
        SCREAMING_SNAKE_CASE_													=  clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'training_function'    )    )
        if secondary_filename is not None:
            SCREAMING_SNAKE_CASE_													=  clean_lines(
                get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,				'training_function'    )    )

    SCREAMING_SNAKE_CASE_													=  'train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n'

    # Specific code in our script that differs from the full version, aka what is new
    SCREAMING_SNAKE_CASE_													=  []
    SCREAMING_SNAKE_CASE_													=  []  # We keep track of the idxs just in case it's a repeated statement
    SCREAMING_SNAKE_CASE_													=  iter(_SCREAMING_SNAKE_CASE    )
    for i in range(len(_SCREAMING_SNAKE_CASE    ) - 1    ):
        if i not in passed_idxs:
            SCREAMING_SNAKE_CASE_													=  next(_SCREAMING_SNAKE_CASE    )
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_feature_code.append(_SCREAMING_SNAKE_CASE    )
                    passed_idxs.append(_SCREAMING_SNAKE_CASE    )
                else:
                    # Skip over the `config['num_epochs'] = 2` statement
                    SCREAMING_SNAKE_CASE_													=  next(_SCREAMING_SNAKE_CASE    )

    # Extract out just the new parts from the full_file_training_func
    SCREAMING_SNAKE_CASE_													=  []
    SCREAMING_SNAKE_CASE_													=  []  # We keep track of the idxs just in case it's a repeated statement
    for i, line in enumerate(_SCREAMING_SNAKE_CASE    ):
        if i not in passed_idxs:
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_full_example_parts.append(_SCREAMING_SNAKE_CASE    )
                    passed_idxs.append(_SCREAMING_SNAKE_CASE    )

    # Finally, get the overall diff
    SCREAMING_SNAKE_CASE_													=  [line for line in new_feature_code if line not in new_full_example_parts]
    if secondary_filename is not None:
        SCREAMING_SNAKE_CASE_													=  [line for line in full_file_contents if line not in secondary_file_func]
        SCREAMING_SNAKE_CASE_													=  [line for line in diff_from_example if line not in diff_from_two]

    return diff_from_example





# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						List[str]    ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_													=  Queue()
    SCREAMING_SNAKE_CASE_													=  [False] * len(_SCREAMING_SNAKE_CASE    )
    SCREAMING_SNAKE_CASE_													=  [-1] * len(_SCREAMING_SNAKE_CASE    )

    def bfs():
        while not queue.empty():
            SCREAMING_SNAKE_CASE_													=  queue.get()
            SCREAMING_SNAKE_CASE_													=  True

            for neighbour in graph[u]:
                if neighbour == u:
                    return False

                if color[neighbour] == -1:
                    SCREAMING_SNAKE_CASE_													=  1 - color[u]
                    queue.put(_SCREAMING_SNAKE_CASE    )

                elif color[neighbour] == color[u]:
                    return False

        return True

    for i in range(len(_SCREAMING_SNAKE_CASE    )    ):
        if not visited[i]:
            queue.put(_SCREAMING_SNAKE_CASE    )
            SCREAMING_SNAKE_CASE_													=  0
            if bfs() is False:
                return False

    return True


if __name__ == "__main__":
       # Adjacency List of graph
       print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))


