

# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter


if TYPE_CHECKING:
    import jax
    import jaxlib

__A			:					List[str]						=			get_logger()

__A			:					Optional[dict]						=			None





class 			_SCREAMING_SNAKE_CASE (   TensorFormatter[Mapping, "jax.Array", Mapping]		):







   '''simple docstring'''




   def __init__(       self					:			Tuple     , __lowerCamelCase					:			Tuple=None     , __lowerCamelCase					:			int=None     , **__lowerCamelCase					:			Dict			):
       super().__init__(features=__lowerCamelCase			)
       import jax
       from jaxlib.xla_client import Device

       if isinstance(__lowerCamelCase     , __lowerCamelCase			):
           raise ValueError(
               f"Expected {device} to be a `str` not {type(__lowerCamelCase			)}, as `jaxlib.xla_extension.Device` "
               "is not serializable neither with `pickle` nor with `dill`. Instead you can surround "
               "the device with `str()` to get its string identifier that will be internally mapped "
               "to the actual `jaxlib.xla_extension.Device`."			)
       SCREAMING_SNAKE_CASE										=   device if isinstance(__lowerCamelCase     , __lowerCamelCase			) else str(jax.devices()[0]			)
       # using global variable since `jaxlib.xla_extension.Device` is not serializable neither
       # with `pickle` nor with `dill`, so we need to use a global variable instead
       global DEVICE_MAPPING
       if DEVICE_MAPPING is None:
           SCREAMING_SNAKE_CASE										=   self._map_devices_to_str()
       if self.device not in list(DEVICE_MAPPING.keys()			):
           logger.warning(
               f"Device with string identifier {self.device} not listed among the available "
               f"devices: {list(DEVICE_MAPPING.keys()			)}, so falling back to the default "
               f"device: {str(jax.devices()[0]			)}."			)
           SCREAMING_SNAKE_CASE										=   str(jax.devices()[0]			)
       SCREAMING_SNAKE_CASE										=   jnp_array_kwargs





   @staticmethod
   def      _snake_case		(       ):
       import jax

       return {str(__lowerCamelCase			): device for device in jax.devices()}





   def      _snake_case		(       self					:			Any     , __lowerCamelCase					:			List[Any]			):
       import jax
       import jax.numpy as jnp

       if isinstance(__lowerCamelCase     , __lowerCamelCase			) and column:
           if all(
               isinstance(__lowerCamelCase     , jax.Array			) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column			):
               return jnp.stack(__lowerCamelCase     , axis=0			)
       return column





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			Dict			):
       import jax
       import jax.numpy as jnp

       if isinstance(__lowerCamelCase     , (str, bytes, type(__lowerCamelCase			))			):
           return value
       elif isinstance(__lowerCamelCase     , (np.character, np.ndarray)			) and np.issubdtype(value.dtype     , np.character			):
           return value.tolist()

       SCREAMING_SNAKE_CASE										=   {}

       if isinstance(__lowerCamelCase     , (np.number, np.ndarray)			) and np.issubdtype(value.dtype     , np.integer			):
           # the default int precision depends on the jax config
           # see https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#double-64bit-precision
           if jax.config.jax_enable_xaa:
               SCREAMING_SNAKE_CASE										=   {"dtype": jnp.intaa}
           else:
               SCREAMING_SNAKE_CASE										=   {"dtype": jnp.intaa}
       elif isinstance(__lowerCamelCase     , (np.number, np.ndarray)			) and np.issubdtype(value.dtype     , np.floating			):
           SCREAMING_SNAKE_CASE										=   {"dtype": jnp.floataa}
       elif config.PIL_AVAILABLE and "PIL" in sys.modules:
           import PIL.Image

           if isinstance(__lowerCamelCase     , PIL.Image.Image			):
               SCREAMING_SNAKE_CASE										=   np.asarray(__lowerCamelCase			)

        # using global variable since `jaxlib.xla_extension.Device` is not serializable neither
        # with `pickle` nor with `dill`, so we need to use a global variable instead
       global DEVICE_MAPPING
       if DEVICE_MAPPING is None:
           SCREAMING_SNAKE_CASE										=   self._map_devices_to_str()

       with jax.default_device(DEVICE_MAPPING[self.device]			):
           # calling jnp.array on a np.ndarray does copy the data
           # see https://github.com/google/jax/issues/4486
           return jnp.array(__lowerCamelCase     , **{**default_dtype, **self.jnp_array_kwargs}			)





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			int			):
       import jax

       # support for torch, tf, jax etc.
       if config.TORCH_AVAILABLE and "torch" in sys.modules:
           import torch

           if isinstance(__lowerCamelCase     , torch.Tensor			):
               return self._tensorize(data_struct.detach().cpu().numpy()[()]			)
       if hasattr(__lowerCamelCase     , "__array__"			) and not isinstance(__lowerCamelCase     , jax.Array			):
           SCREAMING_SNAKE_CASE										=   data_struct.__array__()
       # support for nested types like struct of list of struct
       if isinstance(__lowerCamelCase     , np.ndarray			):
           if data_struct.dtype == object:  # jax arrays cannot be instantied from an array of objects
               return self._consolidate([self.recursive_tensorize(__lowerCamelCase			) for substruct in data_struct]			)
       elif isinstance(__lowerCamelCase     , (list, tuple)			):
           return self._consolidate([self.recursive_tensorize(__lowerCamelCase			) for substruct in data_struct]			)
       return self._tensorize(__lowerCamelCase			)





   def      _snake_case		(       self					:			Union[str, Any]     , __lowerCamelCase					:			dict			):
       return map_nested(self._recursive_tensorize     , __lowerCamelCase     , map_list=__lowerCamelCase			)





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			pa.Table			):
       SCREAMING_SNAKE_CASE										=   self.numpy_arrow_extractor().extract_row(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self.python_features_decoder.decode_row(__lowerCamelCase			)
       return self.recursive_tensorize(__lowerCamelCase			)





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			pa.Table			):
       SCREAMING_SNAKE_CASE										=   self.numpy_arrow_extractor().extract_column(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self.python_features_decoder.decode_column(__lowerCamelCase     , pa_table.column_names[0]			)
       SCREAMING_SNAKE_CASE										=   self.recursive_tensorize(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self._consolidate(__lowerCamelCase			)
       return column





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			pa.Table			):
       SCREAMING_SNAKE_CASE										=   self.numpy_arrow_extractor().extract_batch(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self.python_features_decoder.decode_batch(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self.recursive_tensorize(__lowerCamelCase			)
       for column_name in batch:
           SCREAMING_SNAKE_CASE										=   self._consolidate(batch[column_name]			)
       return batch


from __future__ import annotations

__A			:					str						=			list[tuple[int, int]]

__A			:					Optional[int]						=			[
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

__A			:					List[str]						=			([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right





class 			_SCREAMING_SNAKE_CASE :







   '''simple docstring'''




   def __init__(       self					:			str     , __lowerCamelCase					:			int     , __lowerCamelCase					:			int     , __lowerCamelCase					:			int     , __lowerCamelCase					:			int     , __lowerCamelCase					:			float     , __lowerCamelCase					:			Node | None     , ):
       SCREAMING_SNAKE_CASE										=   pos_x
       SCREAMING_SNAKE_CASE										=   pos_y
       SCREAMING_SNAKE_CASE										=   (pos_y, pos_x)
       SCREAMING_SNAKE_CASE										=   goal_x
       SCREAMING_SNAKE_CASE										=   goal_y
       SCREAMING_SNAKE_CASE										=   g_cost
       SCREAMING_SNAKE_CASE										=   parent
       SCREAMING_SNAKE_CASE										=   self.calculate_heuristic()





   def      _snake_case		(       self					:			Union[str, Any]			):
       SCREAMING_SNAKE_CASE										=   abs(self.pos_x - self.goal_x			)
       SCREAMING_SNAKE_CASE										=   abs(self.pos_y - self.goal_y			)
       return dx + dy





   def __lt__(       self					:			Union[str, Any]     , __lowerCamelCase					:			List[Any]			):
       return self.f_cost < other.f_cost





class 			_SCREAMING_SNAKE_CASE :







   '''simple docstring'''




   def __init__(       self					:			Optional[int]     , __lowerCamelCase					:			tuple[int, int]     , __lowerCamelCase					:			tuple[int, int]			):
       SCREAMING_SNAKE_CASE										=   Node(start[1]     , start[0]     , goal[1]     , goal[0]     , 0     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   Node(goal[1]     , goal[0]     , goal[1]     , goal[0]     , 99999     , __lowerCamelCase			)

       SCREAMING_SNAKE_CASE										=   [self.start]
       SCREAMING_SNAKE_CASE										=   []

       SCREAMING_SNAKE_CASE										=   False





   def      _snake_case		(       self					:			Optional[Any]			):
       while self.open_nodes:
           # Open Nodes are sorted using __lt__
           self.open_nodes.sort()
           SCREAMING_SNAKE_CASE										=   self.open_nodes.pop(0			)

           if current_node.pos == self.target.pos:
               SCREAMING_SNAKE_CASE										=   True
               return self.retrace_path(__lowerCamelCase			)

           self.closed_nodes.append(__lowerCamelCase			)
           SCREAMING_SNAKE_CASE										=   self.get_successors(__lowerCamelCase			)

           for child_node in successors:
               if child_node in self.closed_nodes:
                   continue

               if child_node not in self.open_nodes:
                   self.open_nodes.append(__lowerCamelCase			)
               else:
                   # retrieve the best current path
                   SCREAMING_SNAKE_CASE										=   self.open_nodes.pop(self.open_nodes.index(__lowerCamelCase			)			)

                   if child_node.g_cost < better_node.g_cost:
                       self.open_nodes.append(__lowerCamelCase			)
                   else:
                       self.open_nodes.append(__lowerCamelCase			)

       if not self.reached:
           return [self.start.pos]
       return None





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			Node			):
       SCREAMING_SNAKE_CASE										=   []
       for action in delta:
           SCREAMING_SNAKE_CASE										=   parent.pos_x + action[1]
           SCREAMING_SNAKE_CASE										=   parent.pos_y + action[0]

           if not (0 <= pos_x <= len(grid[0]			) - 1 and 0 <= pos_y <= len(__lowerCamelCase			) - 1):
               continue

           if grid[pos_y][pos_x] != 0:
               continue

           successors.append(
               Node(
                   __lowerCamelCase     , __lowerCamelCase     , self.target.pos_y     , self.target.pos_x     , parent.g_cost + 1     , __lowerCamelCase     , )			)
       return successors





   def      _snake_case		(       self					:			str     , __lowerCamelCase					:			Node | None			):
       SCREAMING_SNAKE_CASE										=   node
       SCREAMING_SNAKE_CASE										=   []
       while current_node is not None:
           path.append((current_node.pos_y, current_node.pos_x)			)
           SCREAMING_SNAKE_CASE										=   current_node.parent
       path.reverse()
       return path


if __name__ == "__main__":
    __A			:					Optional[Any]						=			(0, 0)
    __A			:					Optional[int]						=			(len(grid) - 1, len(grid[0]) - 1)
    for elem in grid:
        print(elem)

    print('------')

    __A			:					List[str]						=			GreedyBestFirst(init, goal)
    __A			:					Tuple						=			greedy_bf.search()
    if path:
        for pos_x, pos_y in path:
            __A			:					Optional[Any]						=			2

        for elem in grid:
            print(elem)