
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      :			Optional[int]					=							get_logger()

_a      :			Optional[dict]					=							None






class      _UpperCAmelCase				(					TensorFormatter[Mapping, """jax.Array""", Mapping]):
    def __init__(    self						,    snake_case_=None						,    snake_case_=None						,    **snake_case_     ):
      super().__init__(features=snake_case_     )
      import jax
      from jaxlib.xla_client import Device

      if isinstance(snake_case_						,    snake_case_     ):
        raise ValueError(
            F'Expected {device} to be a `str` not {type(snake_case_     )}, 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`."     )
      _snake_case     :						Union[str, Any]						=   device if isinstance(snake_case_						,    snake_case_     ) 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:
        _snake_case     :						Tuple						=   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]     )}.'     )
        _snake_case     :						Dict						=   str(jax.devices()[0]     )
      _snake_case     :						List[Any]						=   jnp_array_kwargs
    @staticmethod
    def 					lowerCamelCase__	(    ):
      import jax

      return {str(snake_case_     ): device for device in jax.devices()}
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      import jax
      import jax.numpy as jnp

      if isinstance(snake_case_						,    snake_case_     ) and column:
        if all(
            isinstance(snake_case_						,    jax.Array     ) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column     ):
          return jnp.stack(snake_case_						,    axis=0     )
      return column
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      import jax
      import jax.numpy as jnp

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

      _snake_case     :						Union[str, Any]						=   {}

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

        if isinstance(snake_case_						,    PIL.Image.Image     ):
          _snake_case     :						Optional[Any]						=   np.asarray(snake_case_     )

        # 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:
        _snake_case     :						str						=   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(snake_case_						,    **{**default_dtype, **self.jnp_array_kwargs}     )
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      import jax

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

        if isinstance(snake_case_						,    torch.Tensor     ):
          return self._tensorize(data_struct.detach().cpu().numpy()[()]     )
      if hasattr(snake_case_						,    "__array__"     ) and not isinstance(snake_case_						,    jax.Array     ):
        _snake_case     :						Tuple						=   data_struct.__array__()
      # support for nested types like struct of list of struct
      if isinstance(snake_case_						,    np.ndarray     ):
        if data_struct.dtype == object:  # jax arrays cannot be instantied from an array of objects
          return self._consolidate([self.recursive_tensorize(snake_case_     ) for substruct in data_struct]     )
      elif isinstance(snake_case_						,    (list, tuple)     ):
        return self._consolidate([self.recursive_tensorize(snake_case_     ) for substruct in data_struct]     )
      return self._tensorize(snake_case_     )
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      return map_nested(self._recursive_tensorize						,    snake_case_						,    map_list=snake_case_     )
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      _snake_case     :						List[str]						=   self.numpy_arrow_extractor().extract_row(snake_case_     )
      _snake_case     :						Optional[int]						=   self.python_features_decoder.decode_row(snake_case_     )
      return self.recursive_tensorize(snake_case_     )
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      _snake_case     :						Any						=   self.numpy_arrow_extractor().extract_column(snake_case_     )
      _snake_case     :						Any						=   self.python_features_decoder.decode_column(snake_case_						,    pa_table.column_names[0]     )
      _snake_case     :						Any						=   self.recursive_tensorize(snake_case_     )
      _snake_case     :						str						=   self._consolidate(snake_case_     )
      return column


    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      _snake_case     :						int						=   self.numpy_arrow_extractor().extract_batch(snake_case_     )
      _snake_case     :						Optional[int]						=   self.python_features_decoder.decode_batch(snake_case_     )
      _snake_case     :						Union[str, Any]						=   self.recursive_tensorize(snake_case_     )
      for column_name in batch:
        _snake_case     :						int						=   self._consolidate(batch[column_name]     )
      return batch



"""simple docstring"""
from __future__ import annotations

from collections import namedtuple
def 				a__   (   a   :				float       ,     a   :				float       ,     a   :				float		):

  """simple docstring"""







  _snake_case     :						Optional[Any]						=   namedtuple("result"       ,     "name value"		)
  if (voltage, current, power).count(0		) != 1:
    raise ValueError("Only one argument must be 0"		)
  elif power < 0:
    raise ValueError(
        "Power cannot be negative in any electrical/electronics system"		)
  elif voltage == 0:
    return result("voltage"       ,     power / current		)
  elif current == 0:
    return result("current"       ,     power / voltage		)
  elif power == 0:
    return result("power"       ,     float(round(abs(voltage * current		)       ,     2		)		)		)
  else:
    raise ValueError("Exactly one argument must be 0"		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()

