





# 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

_lowerCamelCase :    Any  							= get_logger()

_lowerCamelCase :    Optional[dict]  							= None


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







							"""simple docstring"""




							def __init__( self     :					Tuple,			_UpperCAmelCase     :					Dict=None,			_UpperCAmelCase     :					Optional[Any]=None,			**_UpperCAmelCase     :					Union[str, Any]						)				->			List[Any]:





														"""simple docstring"""
														super().__init__(features=_UpperCAmelCase						)
														import jax
														from jaxlib.xla_client import Device

														if isinstance(_UpperCAmelCase,			_UpperCAmelCase						):
																					raise ValueError(
																					    F'''Expected {device} to be a `str` not {type(_UpperCAmelCase						)}, 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__       :      Any     =						device if isinstance(_UpperCAmelCase,			_UpperCAmelCase						) 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__       :      Dict     =						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__       :      List[Any]     =						str(jax.devices()[0]						)
														SCREAMING_SNAKE_CASE__       :      str     =						jnp_array_kwargs






							@staticmethod
							def  A_     ( )				->			Dict[str, "jaxlib.xla_extension.Device"]:





														"""simple docstring"""
														import jax

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






							def  A_     ( self     :					str,			_UpperCAmelCase     :					Optional[int]						)				->			str:





														"""simple docstring"""
														import jax
														import jax.numpy as jnp

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






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					int						)				->			Optional[Any]:





														"""simple docstring"""
														import jax
														import jax.numpy as jnp

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

														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						{}

														if isinstance(_UpperCAmelCase,			(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__       :      List[str]     =						{"dtype": jnp.intaa}
																					else:
																												SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						{"dtype": jnp.intaa}
														elif isinstance(_UpperCAmelCase,			(np.number, np.ndarray)						) and np.issubdtype(value.dtype,			np.floating						):
																					SCREAMING_SNAKE_CASE__       :      Tuple     =						{"dtype": jnp.floataa}
														elif config.PIL_AVAILABLE and "PIL" in sys.modules:
																					import PIL.Image

																					if isinstance(_UpperCAmelCase,			PIL.Image.Image						):
																												SCREAMING_SNAKE_CASE__       :      str     =						np.asarray(_UpperCAmelCase						)

        # 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__       :      Optional[int]     =						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(_UpperCAmelCase,			**{**default_dtype, **self.jnp_array_kwargs}						)






							def  A_     ( self     :					Optional[Any],			_UpperCAmelCase     :					int						)				->			Union[str, Any]:





														"""simple docstring"""
														import jax

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

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






							def  A_     ( self     :					Any,			_UpperCAmelCase     :					dict						)				->			int:





														"""simple docstring"""
														return map_nested(self._recursive_tensorize,			_UpperCAmelCase,			map_list=_UpperCAmelCase						)






							def  A_     ( self     :					Dict,			_UpperCAmelCase     :					pa.Table						)				->			Mapping:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.numpy_arrow_extractor().extract_row(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      int     =						self.python_features_decoder.decode_row(_UpperCAmelCase						)
														return self.recursive_tensorize(_UpperCAmelCase						)






							def  A_     ( self     :					str,			_UpperCAmelCase     :					pa.Table						)				->			"jax.Array":





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						self.numpy_arrow_extractor().extract_column(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      List[str]     =						self.python_features_decoder.decode_column(_UpperCAmelCase,			pa_table.column_names[0]						)
														SCREAMING_SNAKE_CASE__       :      Dict     =						self.recursive_tensorize(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						self._consolidate(_UpperCAmelCase						)
														return column






							def  A_     ( self     :					Dict,			_UpperCAmelCase     :					pa.Table						)				->			Mapping:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Tuple     =						self.numpy_arrow_extractor().extract_batch(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Dict     =						self.python_features_decoder.decode_batch(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      List[str]     =						self.recursive_tensorize(_UpperCAmelCase						)
														for column_name in batch:
																					SCREAMING_SNAKE_CASE__       :      List[Any]     =						self._consolidate(batch[column_name]						)
														return batch













class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					int,			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      str     =						name
														SCREAMING_SNAKE_CASE__       :      Tuple     =						val






							def __str__( self     :					str						)				->			List[Any]:





														"""simple docstring"""
														return F'''{self.__class__.__name__}({self.name}, {self.val})'''






							def __lt__( self     :					str,			_UpperCAmelCase     :					Dict						)				->			Union[str, Any]:





														"""simple docstring"""
														return self.val < other.val


class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					Optional[Any],			_UpperCAmelCase     :					str						)				->			Tuple:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						{}
														SCREAMING_SNAKE_CASE__       :      str     =						{}
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.build_heap(_UpperCAmelCase						)






							def __getitem__( self     :					Union[str, Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return self.get_value(_UpperCAmelCase						)






							def  A_     ( self     :					int,			_UpperCAmelCase     :					Optional[int]						)				->			Any:





														"""simple docstring"""
														return (idx - 1) // 2






							def  A_     ( self     :					Optional[Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return idx * 2 + 1






							def  A_     ( self     :					str,			_UpperCAmelCase     :					List[str]						)				->			Union[str, Any]:





														"""simple docstring"""
														return idx * 2 + 2






							def  A_     ( self     :					Tuple,			_UpperCAmelCase     :					int						)				->			Optional[int]:





														"""simple docstring"""
														return self.heap_dict[key]






							def  A_     ( self     :					Optional[int],			_UpperCAmelCase     :					Dict						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      List[str]     =						len(_UpperCAmelCase						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.get_parent_idx(_UpperCAmelCase						)

														for idx, i in enumerate(_UpperCAmelCase						):
																					SCREAMING_SNAKE_CASE__       :      Optional[int]     =						idx
																					SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						i.val

														for i in range(_UpperCAmelCase,			-1,			-1						):
																					self.sift_down(_UpperCAmelCase,			_UpperCAmelCase						)
														return array






							def  A_     ( self     :					List[Any],			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					Tuple						)				->			Tuple:





														"""simple docstring"""
														while True:
																					SCREAMING_SNAKE_CASE__       :      str     =						self.get_left_child_idx(_UpperCAmelCase						)  # noqa: E741
																					SCREAMING_SNAKE_CASE__       :      Tuple     =						self.get_right_child_idx(_UpperCAmelCase						)

																					SCREAMING_SNAKE_CASE__       :      Tuple     =						idx
																					if l < len(_UpperCAmelCase						) and array[l] < array[idx]:
																												SCREAMING_SNAKE_CASE__       :      List[Any]     =						l
																					if r < len(_UpperCAmelCase						) and array[r] < array[smallest]:
																												SCREAMING_SNAKE_CASE__       :      int     =						r

																					if smallest != idx:
																												SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						array[smallest], array[idx]
																												(
																												    (
																												    SCREAMING_SNAKE_CASE__
																												)   ,(
																												    SCREAMING_SNAKE_CASE__
																												)   ,
																												)       :      Optional[Any]     =						(
																												    self.idx_of_element[array[smallest]],
																												    self.idx_of_element[array[idx]],
																												)
																												SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						smallest
																					else:
																												break






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Any:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Any     =						self.get_parent_idx(_UpperCAmelCase						)
														while p >= 0 and self.heap[p] > self.heap[idx]:
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						self.heap[idx], self.heap[p]
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      int     =						(
																					    self.idx_of_element[self.heap[idx]],
																					    self.idx_of_element[self.heap[p]],
																					)
																					SCREAMING_SNAKE_CASE__       :      Dict     =						p
																					SCREAMING_SNAKE_CASE__       :      List[str]     =						self.get_parent_idx(_UpperCAmelCase						)






							def  A_     ( self     :					str						)				->			List[str]:





														"""simple docstring"""
														return self.heap[0]






							def  A_     ( self     :					Tuple						)				->			List[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.heap[-1], self.heap[0]
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      List[Any]     =						(
														    self.idx_of_element[self.heap[-1]],
														    self.idx_of_element[self.heap[0]],
														)

														SCREAMING_SNAKE_CASE__       :      Any     =						self.heap.pop()
														del self.idx_of_element[x]
														self.sift_down(0,			self.heap						)
														return x






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														self.heap.append(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      str     =						len(self.heap						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						node.val
														self.sift_up(len(self.heap						) - 1						)






							def  A_     ( self     :					Optional[int]						)				->			int:





														"""simple docstring"""
														return len(self.heap						) == 0






							def  A_     ( self     :					Any,			_UpperCAmelCase     :					Tuple,			_UpperCAmelCase     :					str						)				->			Dict:





														"""simple docstring"""
														assert (
														    self.heap[self.idx_of_element[node]].val > new_value
														), "newValue must be less that current value"
														SCREAMING_SNAKE_CASE__       :      Tuple     =						new_value
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						new_value
														self.sift_up(self.idx_of_element[node]						)


_lowerCamelCase :    Tuple  							= Node('''R''', -1)
_lowerCamelCase :    int  							= Node('''B''', 6)
_lowerCamelCase :    str  							= Node('''A''', 3)
_lowerCamelCase :    Optional[Any]  							= Node('''X''', 1)
_lowerCamelCase :    str  							= Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
_lowerCamelCase :    int  							= MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
		print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -1_7)

# After
for i in my_min_heap.heap:
		print(i)

if __name__ == "__main__":
		import doctest

		doctest.testmod()






