


'''simple docstring'''



from typing import Any






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   list						,      _SCREAMING_SNAKE_CASE      :   list						,      _SCREAMING_SNAKE_CASE      :   dict						,      _SCREAMING_SNAKE_CASE      :   dict						,      _SCREAMING_SNAKE_CASE      :   dict						,      ):
					_validation(
					    _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      )
					# Creates data structures and fill initial step
					__a			:       dict					    =  {}
					__a			:       dict					    =  {}
					for state in states_space:
										__a			:       List[Any]					    =  observations_space[0]
										__a			:       str					    =  (
										    initial_probabilities[state] * emission_probabilities[state][observation]
										)
										__a			:       List[Any]					    =  None

					# Fills the data structure with the probabilities of
					# different transitions and pointers to previous states
					for o in range(1						,      len(_SCREAMING_SNAKE_CASE   )   ):
										__a			:       str					    =  observations_space[o]
										__a			:       Tuple					    =  observations_space[o - 1]
										for state in states_space:
															# Calculates the argmax for probability function
															__a			:       Optional[Any]					    =  ''
															__a			:       List[str]					    =  -1
															for k_state in states_space:
																				__a			:       Tuple					    =  (
																				    probabilities[(k_state, prior_observation)]
																				    * transition_probabilities[k_state][state]
																				    * emission_probabilities[state][observation]
																				)
																				if probability > max_probability:
																									__a			:       List[Any]					    =  probability
																									__a			:       Dict					    =  k_state

            # Update probabilities and pointers dicts
															__a			:       int					    =  (
															    probabilities[(arg_max, prior_observation)]
															    * transition_probabilities[arg_max][state]
															    * emission_probabilities[state][observation]
															)

															__a			:       Optional[Any]					    =  arg_max

    # The final observation
					__a			:       List[Any]					    =  observations_space[len(_SCREAMING_SNAKE_CASE   ) - 1]

					# argmax for given final observation
					__a			:       str					    =  ''
					__a			:       str					    =  -1
					for k_state in states_space:
										__a			:       Optional[int]					    =  probabilities[(k_state, final_observation)]
										if probability > max_probability:
															__a			:       Dict					    =  probability
															__a			:       Union[str, Any]					    =  k_state
					__a			:       int					    =  arg_max

					# Process pointers backwards
					__a			:       List[str]					    =  last_state
					__a			:       Union[str, Any]					    =  []
					for o in range(len(_SCREAMING_SNAKE_CASE   ) - 1						,      -1						,      -1   ):
										result.append(_SCREAMING_SNAKE_CASE   )
										__a			:       str					    =  pointers[previous, observations_space[o]]
					result.reverse()

					return result






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      ):
					_validate_not_empty(
					    _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      )
					_validate_lists(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )
					_validate_dicts(
					    _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      ):
					if not all(
					    [
					        observations_space,
					        states_space,
					        initial_probabilities,
					        transition_probabilities,
					        emission_probabilities,
					    ]   ):
										raise ValueError('There\'s an empty parameter'   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any   ):
					_validate_list(_SCREAMING_SNAKE_CASE						,      'observations_space'   )
					_validate_list(_SCREAMING_SNAKE_CASE						,      'states_space'   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   str   ):
					if not isinstance(_object						,      _SCREAMING_SNAKE_CASE   ):
										__a			:       Tuple					    =  F"""{var_name} must be a list"""
										raise ValueError(_SCREAMING_SNAKE_CASE   )
					else:
										for x in _object:
															if not isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ):
																				__a			:       Any					    =  F"""{var_name} must be a list of strings"""
																				raise ValueError(_SCREAMING_SNAKE_CASE   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   Any						,      ):
					_validate_dict(_SCREAMING_SNAKE_CASE						,      'initial_probabilities'						,      _SCREAMING_SNAKE_CASE   )
					_validate_nested_dict(_SCREAMING_SNAKE_CASE						,      'transition_probabilities'   )
					_validate_nested_dict(_SCREAMING_SNAKE_CASE						,      'emission_probabilities'   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   str   ):
					_validate_dict(_object						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )
					for x in _object.values():
										_validate_dict(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any						,      _SCREAMING_SNAKE_CASE      :   str						,      _SCREAMING_SNAKE_CASE      :   type						,      _SCREAMING_SNAKE_CASE      :   bool = False   ):
					if not isinstance(_object						,      _SCREAMING_SNAKE_CASE   ):
										__a			:       Any					    =  F"""{var_name} must be a dict"""
										raise ValueError(_SCREAMING_SNAKE_CASE   )
					if not all(isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ) for x in _object   ):
										__a			:       List[str]					    =  F"""{var_name} all keys must be strings"""
										raise ValueError(_SCREAMING_SNAKE_CASE   )
					if not all(isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ) for x in _object.values()   ):
										__a			:       str					    =  'nested dictionary ' if nested else ''
										__a			:       int					    =  F"""{var_name} {nested_text}all values must be {value_type.__name__}"""
										raise ValueError(_SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
	from doctest import testmod

	testmod()







'''simple docstring'''



import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					__a			:       Optional[Any]					    =  tmp_path / 'file.csv'
					__a			:       Union[str, Any]					    =  textwrap.dedent(
					    '\\n        header1,header2\n        1,2\n        10,20\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					__a			:       str					    =  tmp_path / 'malformed_file.csv'
					__a			:       int					    =  textwrap.dedent(
					    '\\n        header1,header2\n        1,2\n        10,20,\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[Any]						,      _SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       Optional[Any]					    =  tmp_path / 'csv_with_image.csv'
					__a			:       Dict					    =  textwrap.dedent(
					    F"""\
        image
        {image_file}
        """   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[Any]   ):
					__a			:       Union[str, Any]					    =  tmp_path / 'csv_with_label.csv'
					__a			:       Any					    =  textwrap.dedent(
					    '\\n        label\n        good\n        bad\n        good\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[Any]   ):
					__a			:       Dict					    =  tmp_path / 'csv_with_int_list.csv'
					__a			:       Tuple					    =  textwrap.dedent(
					    '\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]						,      _SCREAMING_SNAKE_CASE      :   int						,      _SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       int					    =  Csv()
					__a			:       str					    =  csv._generate_tables([[csv_file, malformed_csv_file]]   )
					with pytest.raises(_SCREAMING_SNAKE_CASE						,      match='Error tokenizing data'   ):
										for _ in generator:
															pass
					assert any(
					    record.levelname == 'ERROR'
					    and 'Failed to read file' in record.message
					    and os.path.basename(_SCREAMING_SNAKE_CASE   ) in record.message
					    for record in caplog.records   )






@require_pil
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]   ):
					with open(_SCREAMING_SNAKE_CASE						,      encoding='utf-8'   ) as f:
										__a			:       Tuple					    =  f.read().splitlines()[1]
					__a			:       Tuple					    =  Csv(encoding='utf-8'						,      features=Features({'image': Image()}   )   )
					__a			:       Any					    =  csv._generate_tables([[csv_file_with_image]]   )
					__a			:       int					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa_table.schema.field('image'   ).type == Image()()
					__a			:       Any					    =  pa_table.to_pydict()['image']
					assert generated_content == [{"path": image_file, "bytes": None}]






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					with open(_SCREAMING_SNAKE_CASE						,      encoding='utf-8'   ) as f:
										__a			:       Tuple					    =  f.read().splitlines()[1:]
					__a			:       Optional[int]					    =  Csv(encoding='utf-8'						,      features=Features({'label': ClassLabel(names=['good', 'bad']   )}   )   )
					__a			:       List[str]					    =  csv._generate_tables([[csv_file_with_label]]   )
					__a			:       Dict					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa_table.schema.field('label'   ).type == ClassLabel(names=['good', 'bad']   )()
					__a			:       int					    =  pa_table.to_pydict()['label']
					assert generated_content == [ClassLabel(names=['good', 'bad']   ).straint(_SCREAMING_SNAKE_CASE   ) for label in labels]






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[int]   ):
					__a			:       str					    =  Csv(encoding='utf-8'						,      sep=','						,      converters={'int_list': lambda _SCREAMING_SNAKE_CASE   : [int(_SCREAMING_SNAKE_CASE   ) for i in x.split()]}   )
					__a			:       Any					    =  csv._generate_tables([[csv_file_with_int_list]]   )
					__a			:       Any					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa.types.is_list(pa_table.schema.field('int_list'   ).type   )
					__a			:       Tuple					    =  pa_table.to_pydict()['int_list']
					assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]



