


'''simple docstring'''

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				:Tuple        =      get_logger()

lowerCAmelCase				:Optional[dict]        =      None
class _lowerCamelCase	(						TensorFormatter[Mapping, """jax.Array""", Mapping]							):



		'''simple docstring'''







		def __init__( self		:						List[str]  ,					_A		:						List[str]=None  ,					_A		:						Union[str, Any]=None  ,					**_A		:						List[Any]      )  ->			int:
			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`.'      )
			__magic_name__	:   Union[str, Any]					     =					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:
				__magic_name__	:   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]      )}.'      )
				__magic_name__	:   List[str]					     =					str(jax.devices()[0]      )
			__magic_name__	:   str					     =					jnp_array_kwargs







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

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







		def        __lowerCAmelCase		( self		:						str  ,					_A		:						int      )  ->			str:
			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        __lowerCAmelCase		( self		:						Optional[Any]  ,					_A		:						Optional[int]      )  ->			int:
			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()

			__magic_name__	:   List[Any]					     =					{}

			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:
					__magic_name__	:   str					     =					{'dtype': jnp.intaa}
				else:
					__magic_name__	:   Dict					     =					{'dtype': jnp.intaa}
			elif isinstance(_A  ,					(np.number, np.ndarray)      ) and np.issubdtype(value.dtype  ,					np.floating      ):
				__magic_name__	:   Union[str, Any]					     =					{'dtype': jnp.floataa}
			elif config.PIL_AVAILABLE and "PIL" in sys.modules:
				import PIL.Image

				if isinstance(_A  ,					PIL.Image.Image      ):
					__magic_name__	:   List[Any]					     =					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:
				__magic_name__	:   Union[str, Any]					     =					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        __lowerCAmelCase		( self		:						Any  ,					_A		:						List[Any]      )  ->			Union[str, Any]:
			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      ):
				__magic_name__	:   Union[str, Any]					     =					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        __lowerCAmelCase		( self		:						Union[str, Any]  ,					_A		:						dict      )  ->			Any:
			return map_nested(self._recursive_tensorize  ,					_A  ,					map_list=_A      )







		def        __lowerCAmelCase		( self		:						Union[str, Any]  ,					_A		:						pa.Table      )  ->			Mapping:
			__magic_name__	:   Any					     =					self.numpy_arrow_extractor().extract_row(_A      )
			__magic_name__	:   str					     =					self.python_features_decoder.decode_row(_A      )
			return self.recursive_tensorize(_A      )







		def        __lowerCAmelCase		( self		:						Dict  ,					_A		:						pa.Table      )  ->			"jax.Array":
			__magic_name__	:   int					     =					self.numpy_arrow_extractor().extract_column(_A      )
			__magic_name__	:   Dict					     =					self.python_features_decoder.decode_column(_A  ,					pa_table.column_names[0]      )
			__magic_name__	:   Tuple					     =					self.recursive_tensorize(_A      )
			__magic_name__	:   Tuple					     =					self._consolidate(_A      )
			return column







		def        __lowerCAmelCase		( self		:						List[Any]  ,					_A		:						pa.Table      )  ->			Mapping:
			__magic_name__	:   int					     =					self.numpy_arrow_extractor().extract_batch(_A      )
			__magic_name__	:   Dict					     =					self.python_features_decoder.decode_batch(_A      )
			__magic_name__	:   Any					     =					self.recursive_tensorize(_A      )
			for column_name in batch:
				__magic_name__	:   str					     =					self._consolidate(batch[column_name]      )
			return batch



'''simple docstring'''

def lowerCamelCase      (      lowerCAmelCase    :     str		,		lowerCAmelCase    :     Any		,		lowerCAmelCase    :     Any=False		):





	"""simple docstring"""







	if isinstance(lowerCAmelCase		,		lowerCAmelCase		) and isinstance(lowerCAmelCase		,		lowerCAmelCase		):
		__magic_name__	:   str					     =					len(set_a.intersection(lowerCAmelCase		)		)

		if alternative_union:
			__magic_name__	:   List[str]					     =					len(lowerCAmelCase		) + len(lowerCAmelCase		)
		else:
			__magic_name__	:   Any					     =					len(set_a.union(lowerCAmelCase		)		)

		return intersection / union

	if isinstance(lowerCAmelCase		,		(list, tuple)		) and isinstance(lowerCAmelCase		,		(list, tuple)		):
		__magic_name__	:   str					     =					[element for element in set_a if element in set_b]

		if alternative_union:
			__magic_name__	:   Dict					     =					len(lowerCAmelCase		) + len(lowerCAmelCase		)
			return len(lowerCAmelCase		) / union
		else:
			__magic_name__	:   Any					     =					set_a + [element for element in set_b if element not in set_a]
			return len(lowerCAmelCase		) / len(lowerCAmelCase		)

		return len(lowerCAmelCase		) / len(lowerCAmelCase		)
	return None


if __name__ == "__main__":
							lowerCAmelCase				:Dict        =      {'''a''', '''b''', '''c''', '''d''', '''e'''}
							lowerCAmelCase				:Tuple        =      {'''c''', '''d''', '''e''', '''f''', '''h''', '''i'''}
							print(jaccard_similarity(set_a, set_b))