'''simple docstring'''


import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader






class 					__SCREAMING_SNAKE_CASE						(	lowercase_	):







  '''simple docstring'''






  def __init__(			self				,		snake_case_				,		snake_case_ = None				,		snake_case_ = None				,		snake_case_ = None				,		snake_case_ = False				,		snake_case_ = False				,		snake_case_ = None				,		snake_case_ = None				,		**snake_case_				,		):




       '''simple docstring'''

       super().__init__(
           a__				,		split=a__				,		features=a__				,		cache_dir=a__				,		keep_in_memory=a__				,		streaming=a__				,		num_proc=a__				,		**a__				,		)
       UpperCAmelCase_							:       Any       =				field
       UpperCAmelCase_							:       Union[str, Any]       =				path_or_paths if isinstance(a__				,		a__						) else {self.split: path_or_paths}
       UpperCAmelCase_							:       Optional[int]       =				Json(
           cache_dir=a__				,		data_files=a__				,		features=a__				,		field=a__				,		**a__				,		)






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       if self.streaming:
            UpperCAmelCase_							:       int       =				self.builder.as_streaming_dataset(split=self.split						)
       # Build regular (map-style) dataset
       else:
            UpperCAmelCase_							:       str       =				None
            UpperCAmelCase_							:       int       =				None
            UpperCAmelCase_							:       List[Any]       =				None
            UpperCAmelCase_							:       List[Any]       =				None

            self.builder.download_and_prepare(
                download_config=a__				,		download_mode=a__				,		verification_mode=a__				,		base_path=a__				,		num_proc=self.num_proc				,		)
            UpperCAmelCase_							:       str       =				self.builder.as_dataset(
                split=self.split				,		verification_mode=a__				,		in_memory=self.keep_in_memory						)
       return dataset







class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__(			self				,		snake_case_				,		snake_case_				,		snake_case_ = None				,		snake_case_ = None				,		**snake_case_				,		):




       '''simple docstring'''

       if num_proc is not None and num_proc <= 0:
            raise ValueError(F'''num_proc {num_proc} must be an integer > 0.'''						)

       UpperCAmelCase_							:       Optional[int]       =				dataset
       UpperCAmelCase_							:       Any       =				path_or_buf
       UpperCAmelCase_							:       Union[str, Any]       =				batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
       UpperCAmelCase_							:       str       =				num_proc
       UpperCAmelCase_							:       Tuple       =				'utf-8'
       UpperCAmelCase_							:       Dict       =				to_json_kwargs


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				self.to_json_kwargs.pop('path_or_buf'				,		a__						)
       UpperCAmelCase_							:       Optional[int]       =				self.to_json_kwargs.pop('orient'				,		'records'						)
       UpperCAmelCase_							:       Optional[int]       =				self.to_json_kwargs.pop('lines'				,		True if orient == 'records' else False						)
       UpperCAmelCase_							:       List[str]       =				self.to_json_kwargs.pop('index'				,		False if orient in ['split', 'table'] else True						)
       UpperCAmelCase_							:       Tuple       =				self.to_json_kwargs.pop('compression'				,		a__						)

       if compression not in [None, "infer", "gzip", "bz2", "xz"]:
            raise NotImplementedError(F'''`datasets` currently does not support {compression} compression'''						)

       if isinstance(self.path_or_buf				,		(str, bytes, os.PathLike)						):
            with fsspec.open(self.path_or_buf				,		'wb'				,		compression=a__						) as buffer:
                 UpperCAmelCase_							:       int       =				self._write(file_obj=a__				,		orient=a__				,		lines=a__				,		index=a__				,		**self.to_json_kwargs						)
       else:
            if compression:
                 raise NotImplementedError(
                     F'''The compression parameter is not supported when writing to a buffer, but compression={compression}'''
                     ' was passed. Please provide a local path instead.'						)
            UpperCAmelCase_							:       Union[str, Any]       =				self._write(
                file_obj=self.path_or_buf				,		orient=a__				,		lines=a__				,		index=a__				,		**self.to_json_kwargs						)
       return written


  def _UpperCamelCase					(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_       ,      UpperCAmelCase_       ,      UpperCAmelCase_       ,      UpperCAmelCase_       ,      UpperCAmelCase_							:       List[str]       =				args

       UpperCAmelCase_							:       List[Any]       =				query_table(
           table=self.dataset.data				,		key=slice(a__				,		offset + self.batch_size						)				,		indices=self.dataset._indices				,		)
       UpperCAmelCase_							:       int       =				batch.to_pandas().to_json(
           path_or_buf=a__				,		orient=a__				,		lines=a__				,		index=a__				,		**a__						)
       if not json_str.endswith('\n'						):
            json_str += "\n"
       return json_str.encode(self.encoding						)






  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_				,		snake_case_				,		snake_case_				,		**snake_case_				,		):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				0

       if self.num_proc is None or self.num_proc == 1:
            for offset in logging.tqdm(
                range(0				,		len(self.dataset						)				,		self.batch_size						)				,		unit='ba'				,		disable=not logging.is_progress_bar_enabled()				,		desc='Creating json from Arrow format'				,		):
                 UpperCAmelCase_							:       str       =				self._batch_json((offset, orient, lines, index, to_json_kwargs)						)
                 written += file_obj.write(a__						)
       else:
            UpperCAmelCase_       ,      UpperCAmelCase_							:       Optional[int]       =				len(self.dataset						), self.batch_size
            with multiprocessing.Pool(self.num_proc						) as pool:
                 for json_str in logging.tqdm(
                     pool.imap(
                         self._batch_json				,		[(offset, orient, lines, index, to_json_kwargs) for offset in range(0				,		a__				,		a__						)]				,		)				,		total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size				,		unit='ba'				,		disable=not logging.is_progress_bar_enabled()				,		desc='Creating json from Arrow format'				,		):
                      written += file_obj.write(a__						)

       return written







'''simple docstring'''


from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_						,     lowerCamelCase_	):







  '''simple docstring'''






  @register_to_config
  def __init__(			self				,		snake_case_ = 7_6_8				,		):




       '''simple docstring'''

       super().__init__()

       UpperCAmelCase_							:       int       =				nn.Parameter(torch.zeros(1				,		snake_case_						)						)
       UpperCAmelCase_							:       str       =				nn.Parameter(torch.ones(1				,		snake_case_						)						)


  def _UpperCamelCase					(			self				,		snake_case_ = None				,		snake_case_ = None				,		):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				nn.Parameter(self.mean.to(snake_case_						).to(snake_case_						)						)
       UpperCAmelCase_							:       Tuple       =				nn.Parameter(self.std.to(snake_case_						).to(snake_case_						)						)
       return self


  def _UpperCamelCase					(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Dict       =				(embeds - self.mean) * 1.0 / self.std
       return embeds






  def _UpperCamelCase					(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[Any]       =				(embeds * self.std) + self.mean
       return embeds






