






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

__snake_case												=  get_logger()

__snake_case												=  None







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



      """simple docstring"""
      def __init__(				self    ,				SCREAMING_SNAKE_CASE_=None    ,				SCREAMING_SNAKE_CASE_=None    ,				**SCREAMING_SNAKE_CASE_ )				->      str:
          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`.''' )
          UpperCamelCase       :Dict								=   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:
              UpperCamelCase       :Union[str, Any]								=   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] )}.''' )
              UpperCamelCase       :Dict								=   str(jax.devices()[0] )
          UpperCamelCase       :Tuple								=   jnp_array_kwargs
      @staticmethod
      def     UpperCAmelCase						(				)				->      Dict[str, "jaxlib.xla_extension.Device"]:
          import jax

          return {str(a_ ): device for device in jax.devices()}
      def     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      Optional[Any]:
          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     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      Optional[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()

          UpperCamelCase       :Dict								=   {}

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

              if isinstance(a_    ,				PIL.Image.Image ):
                  UpperCamelCase       :Optional[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:
              UpperCamelCase       :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     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      Optional[int]:
          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 ):
              UpperCamelCase       :List[str]								=   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     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      List[str]:
          return map_nested(self._recursive_tensorize    ,				a_    ,				map_list=a_ )
      def     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      Mapping:
          UpperCamelCase       :Tuple								=   self.numpy_arrow_extractor().extract_row(a_ )
          UpperCamelCase       :List[str]								=   self.python_features_decoder.decode_row(a_ )
          return self.recursive_tensorize(a_ )
      def     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      "jax.Array":
          UpperCamelCase       :List[str]								=   self.numpy_arrow_extractor().extract_column(a_ )
          UpperCamelCase       :List[Any]								=   self.python_features_decoder.decode_column(a_    ,				pa_table.column_names[0] )
          UpperCamelCase       :Any								=   self.recursive_tensorize(a_ )
          UpperCamelCase       :Optional[int]								=   self._consolidate(a_ )
          return column




      def     UpperCAmelCase						(				self    ,				SCREAMING_SNAKE_CASE_ )				->      Mapping:
          UpperCamelCase       :str								=   self.numpy_arrow_extractor().extract_batch(a_ )
          UpperCamelCase       :str								=   self.python_features_decoder.decode_batch(a_ )
          UpperCamelCase       :str								=   self.recursive_tensorize(a_ )
          for column_name in batch:
              UpperCamelCase       :Dict								=   self._consolidate(batch[column_name] )
          return batch










'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import _LazyModule


A_							: int						 =	{"""tokenization_bertweet""": ["""BertweetTokenizer"""]}


if TYPE_CHECKING:
   from .tokenization_bertweet import BertweetTokenizer

else:
   import sys

   A_							: int						 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



