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,
)
UpperCamelCase  							=						logging.getLogger(__name__)

def 			lowercase_				(			_lowerCamelCase							:       str):
    lowercase__ :   Any    					=				git.Repo(search_parent_directories=_lowerCamelCase)
    lowercase__ :   Dict    					=				{
        "repo_id": str(_lowerCamelCase),
        "repo_sha": str(repo.head.object.hexsha),
        "repo_branch": str(repo.active_branch),
    }

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

def 			lowercase_				(			_lowerCamelCase							:       Dict):
    if params.n_gpu <= 0:
        lowercase__ :   str    					=				0
        lowercase__ :   int    					=				-1
        lowercase__ :   Tuple    					=				True
        lowercase__ :   List[Any]    					=				False
        return

    assert torch.cuda.is_available()

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

        lowercase__ :   str    					=				int(os.environ["WORLD_SIZE"])
        lowercase__ :   Any    					=				int(os.environ["N_GPU_NODE"])
        lowercase__ :   int    					=				int(os.environ["RANK"])

        # number of nodes / node ID
        lowercase__ :   Union[str, Any]    					=				params.world_size // params.n_gpu_per_node
        lowercase__ :   str    					=				params.global_rank // params.n_gpu_per_node
        lowercase__ :   Tuple    					=				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

        lowercase__ :   Tuple    					=				1
        lowercase__ :   Any    					=				0
        lowercase__ :   Optional[Any]    					=				0
        lowercase__ :   str    					=				0
        lowercase__ :   Union[str, Any]    					=				1
        lowercase__ :   int    					=				1
        lowercase__ :   int    					=				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
    lowercase__ :   Tuple    					=				params.node_id == 0 and params.local_rank == 0
    lowercase__ :   Dict    					=				params.n_nodes > 1

    # summary
    lowercase__ :   Optional[Any]    					=				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 			lowercase_				(			_lowerCamelCase							:       Any):
    np.random.seed(args.seed)
    torch.manual_seed(args.seed)
    if args.n_gpu > 0:
        torch.cuda.manual_seed_all(args.seed)





from __future__ import annotations

__lowerCamelCase							=       list[list[int]]

# assigning initial values to the grid
__lowerCamelCase							=       [
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
__lowerCamelCase							=       [
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int    ):
       for i in range(9    ):
              if grid[row][i] == n or grid[i][column] == n:
                     return False

       for i in range(3    ):
              for j in range(3    ):
                     if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
                            return False

       return True


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for i in range(9    ):
              for j in range(9    ):
                     if grid[i][j] == 0:
                            return i, j
       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       if location := find_empty_location(__lowerCamelCase    ):
              snake_case				,					snake_case       :   Union[str, Any]							=      location
       else:
              # If the location is ``None``, then the grid is solved.
              return grid

       for digit in range(1				,					10    ):
              if is_safe(__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase    ):
                     snake_case       :   List[Any]							=      digit

                     if sudoku(__lowerCamelCase    ) is not None:
                            return grid

                     snake_case       :   Union[str, Any]							=      0

       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for row in grid:
              for cell in row:
                     print(__lowerCamelCase				,					end=" "    )
              print()


if __name__ == "__main__":
   # make a copy of grid so that you can compare with the unmodified grid
   for example_grid in (initial_grid, no_solution):
      print("""\nExample grid:\n""" + """=""" * 20)
      print_solution(example_grid)
      print("""\nExample grid solution:""")
      __lowerCamelCase							=       sudoku(example_grid)
      if solution is not None:
         print_solution(solution)
      else:
         print("""Cannot find a solution.""")





