


"""simple docstring"""





import json
import logging
import os
import socket

import git
import numpy as np
import torch


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d -  %(message)s''',
    datefmt='''%m/%d/%Y %H:%M:%S''',
    level=logging.INFO,
)
snake_case__		:     Optional[int]    				=				logging.getLogger(__name__)


def      _snake_case						(						_snake_case				:			str			):
      lowerCAmelCase					:	Dict       =   git.Repo(search_parent_directories=_snake_case			)
      lowerCAmelCase					:	int       =   {
          '''repo_id''': str(_snake_case			),
          '''repo_sha''': str(repo.head.object.hexsha			),
          '''repo_branch''': str(repo.active_branch			),
      }

      with open(os.path.join(_snake_case ,   '''git_log.json'''			) ,   '''w'''			) as f:
            json.dump(_snake_case ,   _snake_case ,   indent=4			)


def      _snake_case						(						_snake_case				:			List[str]			):
      if params.n_gpu <= 0:
            lowerCAmelCase					:	int       =   0
            lowerCAmelCase					:	Optional[int]       =   -1
            lowerCAmelCase					:	List[str]       =   True
            lowerCAmelCase					:	List[str]       =   False
            return

      assert torch.cuda.is_available()

      logger.info('''Initializing GPUs'''			)
      if params.n_gpu > 1:
            assert params.local_rank != -1

            lowerCAmelCase					:	int       =   int(os.environ['''WORLD_SIZE''']			)
            lowerCAmelCase					:	str       =   int(os.environ['''N_GPU_NODE''']			)
            lowerCAmelCase					:	Any       =   int(os.environ['''RANK''']			)

            # number of nodes / node ID
            lowerCAmelCase					:	str       =   params.world_size // params.n_gpu_per_node
            lowerCAmelCase					:	Optional[int]       =   params.global_rank // params.n_gpu_per_node
            lowerCAmelCase					:	Any       =   True

            assert params.n_nodes == int(os.environ['''N_NODES''']			)
            assert params.node_id == int(os.environ['''NODE_RANK''']			)

      # local job (single GPU)
      else:
            assert params.local_rank == -1

            lowerCAmelCase					:	int       =   1
            lowerCAmelCase					:	int       =   0
            lowerCAmelCase					:	Optional[Any]       =   0
            lowerCAmelCase					:	Union[str, Any]       =   0
            lowerCAmelCase					:	Any       =   1
            lowerCAmelCase					:	Any       =   1
            lowerCAmelCase					:	Any       =   False

      # sanity checks
      assert params.n_nodes >= 1
      assert 0 <= params.node_id < params.n_nodes
      assert 0 <= params.local_rank <= params.global_rank < params.world_size
      assert params.world_size == params.n_nodes * params.n_gpu_per_node

      # define whether this is the master process / if we are in multi-node distributed mode
      lowerCAmelCase					:	int       =   params.node_id == 0 and params.local_rank == 0
      lowerCAmelCase					:	str       =   params.n_nodes > 1

      # summary
      lowerCAmelCase					:	List[str]       =   f'''--- Global rank: {params.global_rank} - '''
      logger.info(PREFIX + '''Number of nodes: %i''' % params.n_nodes			)
      logger.info(PREFIX + '''Node ID        : %i''' % params.node_id			)
      logger.info(PREFIX + '''Local rank     : %i''' % params.local_rank			)
      logger.info(PREFIX + '''World size     : %i''' % params.world_size			)
      logger.info(PREFIX + '''GPUs per node  : %i''' % params.n_gpu_per_node			)
      logger.info(PREFIX + '''Master         : %s''' % str(params.is_master			)			)
      logger.info(PREFIX + '''Multi-node     : %s''' % str(params.multi_node			)			)
      logger.info(PREFIX + '''Multi-GPU      : %s''' % str(params.multi_gpu			)			)
      logger.info(PREFIX + '''Hostname       : %s''' % socket.gethostname()			)

      # set GPU device
      torch.cuda.set_device(params.local_rank			)

      # initialize multi-GPU
      if params.multi_gpu:
            logger.info('''Initializing PyTorch distributed'''			)
            torch.distributed.init_process_group(
                init_method='''env://''' ,   backend='''nccl''' ,   )






def      _snake_case						(						_snake_case				:			Dict			):
      np.random.seed(args.seed			)
      torch.manual_seed(args.seed			)
      if args.n_gpu > 0:
            torch.cuda.manual_seed_all(args.seed			)






"""simple docstring"""





# using dfs for finding eulerian path traversal


def      _snake_case						(						_snake_case				:			Optional[Any] ,   _snake_case				:			List[Any] ,   _snake_case				:			str ,   _snake_case				:			List[Any]=None			):
      lowerCAmelCase					:	Any       =   (path or []) + [u]
      for v in graph[u]:
            if visited_edge[u][v] is False:
                  lowerCAmelCase,      lowerCAmelCase					:	Union[str, Any]       =   True, True
                  lowerCAmelCase					:	int       =   dfs(_snake_case ,   _snake_case ,   _snake_case ,   _snake_case			)
      return path


def      _snake_case						(						_snake_case				:			Optional[int] ,   _snake_case				:			Dict			):
      lowerCAmelCase					:	Tuple       =   0
      lowerCAmelCase					:	Optional[Any]       =   -1
      for i in range(_snake_case			):
            if i not in graph.keys():
                  continue
            if len(graph[i]			) % 2 == 1:
                  odd_degree_nodes += 1
                  lowerCAmelCase					:	Optional[Any]       =   i
      if odd_degree_nodes == 0:
            return 1, odd_node
      if odd_degree_nodes == 2:
            return 2, odd_node
      return 3, odd_node


def      _snake_case						(						_snake_case				:			Tuple ,   _snake_case				:			List[Any]			):
      lowerCAmelCase					:	Any       =   [[False for _ in range(max_node + 1			)] for _ in range(max_node + 1			)]
      lowerCAmelCase,      lowerCAmelCase					:	Optional[int]       =   check_circuit_or_path(_snake_case ,   _snake_case			)
      if check == 3:
            print('''graph is not Eulerian'''			)
            print('''no path'''			)
            return
      lowerCAmelCase					:	Dict       =   1
      if check == 2:
            lowerCAmelCase					:	int       =   odd_node
            print('''graph has a Euler path'''			)
      if check == 1:
            print('''graph has a Euler cycle'''			)
      lowerCAmelCase					:	List[str]       =   dfs(_snake_case ,   _snake_case ,   _snake_case			)
      print(_snake_case			)


def      _snake_case						(						):
      lowerCAmelCase					:	Optional[Any]       =   {1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
      lowerCAmelCase					:	Union[str, Any]       =   {1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
      lowerCAmelCase					:	List[Any]       =   {1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
      lowerCAmelCase					:	Optional[Any]       =   {1: [2, 3], 2: [1, 3], 3: [1, 2]}
      lowerCAmelCase					:	Any       =   {
          1: [],
          2: []
          # all degree is zero
      }
      lowerCAmelCase					:	List[str]       =   10
      check_euler(_snake_case ,   _snake_case			)
      check_euler(_snake_case ,   _snake_case			)
      check_euler(_snake_case ,   _snake_case			)
      check_euler(_snake_case ,   _snake_case			)
      check_euler(_snake_case ,   _snake_case			)


if __name__ == "__main__":
 main()


