'''simple docstring'''





import html

from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends


if is_bsa_available():
    import bsa
    from bsa import BeautifulSoup


SCREAMING_SNAKE_CASE_:					Dict  =logging.get_logger(__name__)




class 	__A				(			UpperCamelCase__     ):



    def __init__(self   :   Optional[Any]       ,      **__a   :   Tuple			):
         requires_backends(self       ,      ["bs4"]			)
         super().__init__(**__a			)



    def  _lowercase						(self   :   Union[str, Any]       ,      __a   :   Union[str, Any]			):
         UpperCAmelCase_	   =       []
         UpperCAmelCase_	   =       []
         UpperCAmelCase_	   =       element if element.name else element.parent
         for parent in child.parents:  # type: bs4.element.Tag
              UpperCAmelCase_	   =       parent.find_all(child.name       ,      recursive=__a			)
              xpath_tags.append(child.name			)
              xpath_subscripts.append(
                  0 if 1 == len(__a			) else next(i for i, s in enumerate(__a       ,      1			) if s is child			)			)
              UpperCAmelCase_	   =       parent
         xpath_tags.reverse()
         xpath_subscripts.reverse()
         return xpath_tags, xpath_subscripts



    def  _lowercase						(self   :   Tuple       ,      __a   :   Optional[Any]			):
         UpperCAmelCase_	   =       BeautifulSoup(__a       ,      "html.parser"			)

         UpperCAmelCase_	   =       []
         UpperCAmelCase_	   =       []
         UpperCAmelCase_	   =       []

         for element in html_code.descendants:
              if type(__a			) == bsa.element.NavigableString:
                   if type(element.parent			) != bsa.element.Tag:
                        continue

                   UpperCAmelCase_	   =       html.unescape(__a			).strip()
                   if not text_in_this_tag:
                        continue

                   all_doc_strings.append(__a			)

                   UpperCAmelCase_   ,			UpperCAmelCase_	   =       self.xpath_soup(__a			)
                   stringaxtag_seq.append(__a			)
                   stringaxsubs_seq.append(__a			)

         if len(__a			) != len(__a			):
              raise ValueError("Number of doc strings and xtags does not correspond"			)
         if len(__a			) != len(__a			):
              raise ValueError("Number of doc strings and xsubs does not correspond"			)

         return all_doc_strings, stringaxtag_seq, stringaxsubs_seq



    def  _lowercase						(self   :   str       ,      __a   :   List[str]       ,      __a   :   Any			):
         UpperCAmelCase_	   =       ""
         for tagname, subs in zip(__a       ,      __a			):
              xpath += f"""/{tagname}"""
              if subs != 0:
                   xpath += f"""[{subs}]"""
         return xpath






    def __call__(self   :   int       ,      __a   :   Tuple			):
         UpperCAmelCase_	   =       False

         # Check that strings has a valid type
         if isinstance(__a       ,      __a			):
              UpperCAmelCase_	   =       True
         elif isinstance(__a       ,      (list, tuple)			):
              if len(__a			) == 0 or isinstance(html_strings[0]       ,      __a			):
                   UpperCAmelCase_	   =       True

         if not valid_strings:
              raise ValueError(
                  "HTML strings must of type `str`, `List[str]` (batch of examples), "
                  f"""but is of type {type(__a			)}."""			)

         UpperCAmelCase_	   =       bool(isinstance(__a       ,      (list, tuple)			) and (isinstance(html_strings[0]       ,      __a			))			)

         if not is_batched:
              UpperCAmelCase_	   =       [html_strings]

         # Get nodes + xpaths
         UpperCAmelCase_	   =       []
         UpperCAmelCase_	   =       []
         for html_string in html_strings:
              UpperCAmelCase_   ,			UpperCAmelCase_   ,			UpperCAmelCase_	   =       self.get_three_from_single(__a			)
              nodes.append(__a			)
              UpperCAmelCase_	   =       []
              for node, tag_list, sub_list in zip(__a       ,      __a       ,      __a			):
                   UpperCAmelCase_	   =       self.construct_xpath(__a       ,      __a			)
                   xpath_strings.append(__a			)
              xpaths.append(__a			)

         # return as Dict
         UpperCAmelCase_	   =       {"nodes": nodes, "xpaths": xpaths}
         UpperCAmelCase_	   =       BatchFeature(data=__a       ,      tensor_type=__a			)

         return encoded_inputs





'''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

SCREAMING_SNAKE_CASE_:					List[str]  =get_logger()

SCREAMING_SNAKE_CASE_:					Optional[dict]  =None




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



    def __init__(self   :   List[Any]       ,      __a   :   Optional[int]=None       ,      __a   :   Any=None       ,      **__a   :   Dict			):
         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_	   =       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_	   =       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_	   =       str(jax.devices()[0]			)
         UpperCAmelCase_	   =       jnp_array_kwargs



    @staticmethod
    def  _lowercase						():
         import jax

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



    def  _lowercase						(self   :   str       ,      __a   :   Tuple			):
         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  _lowercase						(self   :   Any       ,      __a   :   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_	   =       {}

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

              if isinstance(__a       ,      PIL.Image.Image			):
                   UpperCAmelCase_	   =       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_	   =       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  _lowercase						(self   :   int       ,      __a   :   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			):
              UpperCAmelCase_	   =       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  _lowercase						(self   :   Union[str, Any]       ,      __a   :   dict			):
         return map_nested(self._recursive_tensorize       ,      __a       ,      map_list=__a			)



    def  _lowercase						(self   :   str       ,      __a   :   pa.Table			):
         UpperCAmelCase_	   =       self.numpy_arrow_extractor().extract_row(__a			)
         UpperCAmelCase_	   =       self.python_features_decoder.decode_row(__a			)
         return self.recursive_tensorize(__a			)



    def  _lowercase						(self   :   Tuple       ,      __a   :   pa.Table			):
         UpperCAmelCase_	   =       self.numpy_arrow_extractor().extract_column(__a			)
         UpperCAmelCase_	   =       self.python_features_decoder.decode_column(__a       ,      pa_table.column_names[0]			)
         UpperCAmelCase_	   =       self.recursive_tensorize(__a			)
         UpperCAmelCase_	   =       self._consolidate(__a			)
         return column






    def  _lowercase						(self   :   str       ,      __a   :   pa.Table			):
         UpperCAmelCase_	   =       self.numpy_arrow_extractor().extract_batch(__a			)
         UpperCAmelCase_	   =       self.python_features_decoder.decode_batch(__a			)
         UpperCAmelCase_	   =       self.recursive_tensorize(__a			)
         for column_name in batch:
              UpperCAmelCase_	   =       self._consolidate(batch[column_name]			)
         return batch




