



'''simple docstring'''





# 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

lowercase_									=    get_logger()

lowercase_									=    None






class __A     (    TensorFormatter[Mapping, 'jax.Array', Mapping]		):



 '''simple docstring'''







 def __init__(self					,  A=None					,  A=None					,  **A			)       ->	List[str]:


      """simple docstring"""



      super().__init__(features=A			)
      import jax
      from jaxlib.xla_client import Device

      if isinstance(A					,  A			):
           raise ValueError(
               f'''Expected {device} to be a `str` not {type(A			)}, 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`.'''			)
      _a           =    device if isinstance(A					,  A			) 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:
           _a           =    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]			)}.'''			)
           _a           =    str(jax.devices()[0]			)
      _a           =    jnp_array_kwargs



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


      """simple docstring"""



      import jax

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



 def    a__    (self					,  A			)       ->	int:


      """simple docstring"""



      import jax
      import jax.numpy as jnp

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



 def    a__    (self					,  A			)       ->	str:


      """simple docstring"""



      import jax
      import jax.numpy as jnp

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

      _a           =    {}

      if isinstance(A					,  (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:
                _a           =    {'''dtype''': jnp.intaa}
           else:
                _a           =    {'''dtype''': jnp.intaa}
      elif isinstance(A					,  (np.number, np.ndarray)			) and np.issubdtype(value.dtype					,  np.floating			):
           _a           =    {'''dtype''': jnp.floataa}
      elif config.PIL_AVAILABLE and "PIL" in sys.modules:
           import PIL.Image

           if isinstance(A					,  PIL.Image.Image			):
                _a           =    np.asarray(A			)

        # 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:
           _a           =    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(A					,  **{**default_dtype, **self.jnp_array_kwargs}			)



 def    a__    (self					,  A			)       ->	Optional[int]:


      """simple docstring"""



      import jax

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

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



 def    a__    (self					,  A			)       ->	Dict:


      """simple docstring"""



      return map_nested(self._recursive_tensorize					,  A					,  map_list=A			)



 def    a__    (self					,  A			)       ->	Mapping:


      """simple docstring"""



      _a           =    self.numpy_arrow_extractor().extract_row(A			)
      _a           =    self.python_features_decoder.decode_row(A			)
      return self.recursive_tensorize(A			)



 def    a__    (self					,  A			)       ->	"jax.Array":


      """simple docstring"""



      _a           =    self.numpy_arrow_extractor().extract_column(A			)
      _a           =    self.python_features_decoder.decode_column(A					,  pa_table.column_names[0]			)
      _a           =    self.recursive_tensorize(A			)
      _a           =    self._consolidate(A			)
      return column



 def    a__    (self					,  A			)       ->	Mapping:


      """simple docstring"""



      _a           =    self.numpy_arrow_extractor().extract_batch(A			)
      _a           =    self.python_features_decoder.decode_batch(A			)
      _a           =    self.recursive_tensorize(A			)
      for column_name in batch:
           _a           =    self._consolidate(batch[column_name]			)
      return batch











'''simple docstring'''



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE							=						{
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
SCREAMING_SNAKE_CASE							=						'ETAOINSHRDLCUMWFGYPBVKJXQZ'
SCREAMING_SNAKE_CASE							=						'ABCDEFGHIJKLMNOPQRSTUVWXYZ'


def 				lowercase_					(     __A			:							str      )							->   dict[str, int]:



 """simple docstring"""




 lowercase       : List[str]						={letter: 0 for letter in string.ascii_uppercase}
 for letter in message.upper():
  if letter in LETTERS:
   letter_count[letter] += 1

 return letter_count


def 				lowercase_					(     __A			:							tuple      )							->   str:



 """simple docstring"""




 return x[0]


def 				lowercase_					(     __A			:							str      )							->   str:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_letter_count(__A      )
 lowercase       : dict[int, list[str]]						={
     freq: [] for letter, freq in letter_to_freq.items()
 }
 for letter in LETTERS:
  freq_to_letter[letter_to_freq[letter]].append(__A      )

 lowercase       : dict[int, str]						={}

 for freq in freq_to_letter:
  freq_to_letter[freq].sort(key=ETAOIN.find       ,   reverse=__A      )
  lowercase       : Optional[int]						=''''''.join(freq_to_letter[freq]      )

 lowercase       : str						=list(freq_to_letter_str.items()      )
 freq_pairs.sort(key=__A       ,   reverse=__A      )

 lowercase       : list[str]						=[freq_pair[1] for freq_pair in freq_pairs]

 return "".join(__A      )


def 				lowercase_					(     __A			:							str      )							->   int:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_frequency_order(__A      )
 lowercase       : Union[str, Any]						=0
 for common_letter in ETAOIN[:6]:
  if common_letter in freq_order[:6]:
   match_score += 1

 for uncommon_letter in ETAOIN[-6:]:
  if uncommon_letter in freq_order[-6:]:
   match_score += 1

 return match_score


if __name__ == "__main__":
      import doctest

      doctest.testmod()



