




"""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

_A													=      get_logger()

_A													=      None


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






   def __init__(		self       :		Dict   ,     UpperCamelCase       :		Any=None   ,     UpperCamelCase       :		int=None   ,     **UpperCamelCase       :		str   )			->						List[Any]:

         """simple docstring"""
         super().__init__(features=UpperCamelCase   )
         import jax
         from jaxlib.xla_client import Device

         if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
               raise ValueError(
                   f"""Expected {device} to be a `str` not {type(UpperCamelCase   )}, 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`."""   )
         lowerCAmelCase__      :			Dict   =	device if isinstance(UpperCamelCase   ,     UpperCamelCase   ) 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:
               lowerCAmelCase__      :			Optional[int]   =	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]   )}."""   )
               lowerCAmelCase__      :			int   =	str(jax.devices()[0]   )
         lowerCAmelCase__      :			Optional[Any]   =	jnp_array_kwargs






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

         """simple docstring"""
         import jax

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






   def 	_lowerCAmelCase   (		self       :		List[str]   ,     UpperCamelCase       :		Dict   )			->						str:

         """simple docstring"""
         import jax
         import jax.numpy as jnp

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






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   ,     UpperCamelCase       :		int   )			->						str:

         """simple docstring"""
         import jax
         import jax.numpy as jnp

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

         lowerCAmelCase__      :			List[str]   =	{}

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

               if isinstance(UpperCamelCase   ,     PIL.Image.Image   ):
                     lowerCAmelCase__      :			Union[str, Any]   =	np.asarray(UpperCamelCase   )

        # 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:
               lowerCAmelCase__      :			int   =	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(UpperCamelCase   ,     **{**default_dtype, **self.jnp_array_kwargs}   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     UpperCamelCase       :		Dict   )			->						List[Any]:

         """simple docstring"""
         import jax

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

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






   def 	_lowerCAmelCase   (		self       :		int   ,     UpperCamelCase       :		dict   )			->						Optional[Any]:

         """simple docstring"""
         return map_nested(self._recursive_tensorize   ,     UpperCamelCase   ,     map_list=UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   ,     UpperCamelCase       :		pa.Table   )			->						Mapping:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	self.numpy_arrow_extractor().extract_row(UpperCamelCase   )
         lowerCAmelCase__      :			Union[str, Any]   =	self.python_features_decoder.decode_row(UpperCamelCase   )
         return self.recursive_tensorize(UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     UpperCamelCase       :		pa.Table   )			->						"jax.Array":

         """simple docstring"""
         lowerCAmelCase__      :			Union[str, Any]   =	self.numpy_arrow_extractor().extract_column(UpperCamelCase   )
         lowerCAmelCase__      :			List[str]   =	self.python_features_decoder.decode_column(UpperCamelCase   ,     pa_table.column_names[0]   )
         lowerCAmelCase__      :			Any   =	self.recursive_tensorize(UpperCamelCase   )
         lowerCAmelCase__      :			Optional[Any]   =	self._consolidate(UpperCamelCase   )
         return column






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     UpperCamelCase       :		pa.Table   )			->						Mapping:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	self.numpy_arrow_extractor().extract_batch(UpperCamelCase   )
         lowerCAmelCase__      :			Optional[int]   =	self.python_features_decoder.decode_batch(UpperCamelCase   )
         lowerCAmelCase__      :			int   =	self.recursive_tensorize(UpperCamelCase   )
         for column_name in batch:
               lowerCAmelCase__      :			Any   =	self._consolidate(batch[column_name]   )
         return batch











"""simple docstring"""


import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_A													=      logging.getLogger(__name__)


class _lowerCamelCase    (					a_						):






   def __init__(		self       :		List[Any]   ,     UpperCamelCase       :		Dict=-1   )			->						List[Any]:

         """simple docstring"""
         # in NER datasets, the last column is usually reserved for NER label
         lowerCAmelCase__      :			Optional[int]   =	label_idx






   def 	_lowerCAmelCase   (		self       :		Optional[int]   ,     UpperCamelCase       :		Optional[int]   ,     UpperCamelCase       :		Union[Split, str]   )			->						List[InputExample]:

         """simple docstring"""
         if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
               lowerCAmelCase__      :			int   =	mode.value
         lowerCAmelCase__      :			Dict   =	os.path.join(UpperCamelCase   ,     f"""{mode}.txt"""   )
         lowerCAmelCase__      :			str   =	1
         lowerCAmelCase__      :			List[Any]   =	[]
         with open(UpperCamelCase   ,     encoding="""utf-8"""   ) as f:
               lowerCAmelCase__      :			str   =	[]
               lowerCAmelCase__      :			Any   =	[]
               for line in f:
                     if line.startswith("""-DOCSTART-"""   ) or line == "" or line == "\n":
                           if words:
                                 examples.append(InputExample(guid=f"""{mode}-{guid_index}"""   ,     words=UpperCamelCase   ,     labels=UpperCamelCase   )   )
                                 guid_index += 1
                                 lowerCAmelCase__      :			Optional[Any]   =	[]
                                 lowerCAmelCase__      :			Tuple   =	[]
                     else:
                           lowerCAmelCase__      :			Optional[int]   =	line.split(""" """   )
                           words.append(splits[0]   )
                           if len(UpperCamelCase   ) > 1:
                                 labels.append(splits[self.label_idx].replace("""\n"""   ,     """"""   )   )
                           else:
                                 # Examples could have no label for mode = "test"
                                 labels.append("""O"""   )
               if words:
                     examples.append(InputExample(guid=f"""{mode}-{guid_index}"""   ,     words=UpperCamelCase   ,     labels=UpperCamelCase   )   )
         return examples






   def 	_lowerCAmelCase   (		self       :		Any   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		List   )			->						List[Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	0
         for line in test_input_reader:
               if line.startswith("""-DOCSTART-"""   ) or line == "" or line == "\n":
                     writer.write(UpperCamelCase   )
                     if not preds_list[example_id]:
                           example_id += 1
               elif preds_list[example_id]:
                     lowerCAmelCase__      :			Union[str, Any]   =	line.split()[0] + """ """ + preds_list[example_id].pop(0   ) + """\n"""
                     writer.write(UpperCamelCase   )
               else:
                     logger.warning("""Maximum sequence length exceeded: No prediction for '%s'."""   ,     line.split()[0]   )






   def 	_lowerCAmelCase   (		self       :		str   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """r"""   ) as f:
                     lowerCAmelCase__      :			Any   =	f.read().splitlines()
               if "O" not in labels:
                     lowerCAmelCase__      :			List[str]   =	["""O"""] + labels
               return labels
         else:
               return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]






class _lowerCamelCase    (					a_						):






   def __init__(		self       :		Union[str, Any]   )			->						Any:

         """simple docstring"""
         # in CONLL2003 dataset chunk column is second-to-last
         super().__init__(label_idx=-2   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """r"""   ) as f:
                     lowerCAmelCase__      :			Any   =	f.read().splitlines()
               if "O" not in labels:
                     lowerCAmelCase__      :			str   =	["""O"""] + labels
               return labels
         else:
               return [
                   "O",
                   "B-ADVP",
                   "B-INTJ",
                   "B-LST",
                   "B-PRT",
                   "B-NP",
                   "B-SBAR",
                   "B-VP",
                   "B-ADJP",
                   "B-CONJP",
                   "B-PP",
                   "I-ADVP",
                   "I-INTJ",
                   "I-LST",
                   "I-PRT",
                   "I-NP",
                   "I-SBAR",
                   "I-VP",
                   "I-ADJP",
                   "I-CONJP",
                   "I-PP",
               ]






class _lowerCamelCase    (					a_						):






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   ,     UpperCamelCase       :		Any   ,     UpperCamelCase       :		Union[Split, str]   )			->						List[InputExample]:

         """simple docstring"""
         if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
               lowerCAmelCase__      :			Optional[Any]   =	mode.value
         lowerCAmelCase__      :			int   =	os.path.join(UpperCamelCase   ,     f"""{mode}.txt"""   )
         lowerCAmelCase__      :			Optional[int]   =	1
         lowerCAmelCase__      :			List[Any]   =	[]

         with open(UpperCamelCase   ,     encoding="""utf-8"""   ) as f:
               for sentence in parse_incr(UpperCamelCase   ):
                     lowerCAmelCase__      :			Union[str, Any]   =	[]
                     lowerCAmelCase__      :			List[Any]   =	[]
                     for token in sentence:
                           words.append(token["""form"""]   )
                           labels.append(token["""upos"""]   )
                     assert len(UpperCamelCase   ) == len(UpperCamelCase   )
                     if words:
                           examples.append(InputExample(guid=f"""{mode}-{guid_index}"""   ,     words=UpperCamelCase   ,     labels=UpperCamelCase   )   )
                           guid_index += 1
         return examples






   def 	_lowerCAmelCase   (		self       :		List[str]   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		List   )			->						List[Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Any   =	0
         for sentence in parse_incr(UpperCamelCase   ):
               lowerCAmelCase__      :			Union[str, Any]   =	preds_list[example_id]
               lowerCAmelCase__      :			List[Any]   =	""""""
               for token in sentence:
                     out += f"""{token['form']} ({token['upos']}|{s_p.pop(0   )}) """
               out += "\n"
               writer.write(UpperCamelCase   )
               example_id += 1






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """r"""   ) as f:
                     return f.read().splitlines()
         else:
               return [
                   "ADJ",
                   "ADP",
                   "ADV",
                   "AUX",
                   "CCONJ",
                   "DET",
                   "INTJ",
                   "NOUN",
                   "NUM",
                   "PART",
                   "PRON",
                   "PROPN",
                   "PUNCT",
                   "SCONJ",
                   "SYM",
                   "VERB",
                   "X",
               ]





