"""simple docstring"""





import json
import os
import shutil
import tempfile
import unittest

from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_wavaveca import floats_list


class 					UpperCAmelCase_     (   unittest.TestCase):


						def 		_UpperCAmelCase	(       self							)	-> Union[str, Any]:
													lowercase__      :		Any          =     '<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K \' X J Q Z'.split(' '							)
													lowercase__      :		Optional[int]          =     dict(zip(snake_case__		,      range(len(snake_case__							)							)							)							)

													lowercase__      :		Optional[Any]          =     {
													    'pad_token': '<pad>',
													    'unk_token': '<unk>',
													    'bos_token': '<s>',
													    'eos_token': '</s>',
													}
													lowercase__      :		str          =     {
													    'feature_size': 1,
													    'padding_value': 0.0,
													    'sampling_rate': 1_6_0_0_0,
													    'return_attention_mask': False,
													    'do_normalize': True,
													}

													lowercase__      :		Dict          =     tempfile.mkdtemp()
													lowercase__      :		Optional[int]          =     os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES['vocab_file']							)
													lowercase__      :		Optional[Any]          =     os.path.join(self.tmpdirname		,      snake_case__							)
													with open(self.vocab_file		,      'w'		,      encoding='utf-8'							) as fp:
																				fp.write(json.dumps(snake_case__							) + '\n'							)

													with open(self.feature_extraction_file		,      'w'		,      encoding='utf-8'							) as fp:
																				fp.write(json.dumps(snake_case__							) + '\n'							)


						def 		_UpperCAmelCase	(       self		,      **a							)	-> Optional[Any]:
													lowercase__      :		str          =     self.add_kwargs_tokens_map.copy()
													kwargs.update(snake_case__							)
													return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname		,      **snake_case__							)


						def 		_UpperCAmelCase	(       self		,      **a							)	-> Any:
													return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname		,      **snake_case__							)


						def 		_UpperCAmelCase	(       self							)	-> str:
													shutil.rmtree(self.tmpdirname							)


						def 		_UpperCAmelCase	(       self							)	-> Dict:
													lowercase__      :		str          =     self.get_tokenizer()
													lowercase__      :		List[str]          =     self.get_feature_extractor()

													lowercase__      :		str          =     WavaVecaProcessor(tokenizer=snake_case__		,      feature_extractor=snake_case__							)

													processor.save_pretrained(self.tmpdirname							)
													lowercase__      :		Optional[Any]          =     WavaVecaProcessor.from_pretrained(self.tmpdirname							)

													self.assertEqual(processor.tokenizer.get_vocab()		,      tokenizer.get_vocab()							)
													self.assertIsInstance(processor.tokenizer		,      snake_case__							)

													self.assertEqual(processor.feature_extractor.to_json_string()		,      feature_extractor.to_json_string()							)
													self.assertIsInstance(processor.feature_extractor		,      snake_case__							)


						def 		_UpperCAmelCase	(       self							)	-> List[str]:
													lowercase__      :		int          =     WavaVecaProcessor(tokenizer=self.get_tokenizer()		,      feature_extractor=self.get_feature_extractor()							)
													processor.save_pretrained(self.tmpdirname							)

													lowercase__      :		Tuple          =     self.get_tokenizer(bos_token='(BOS)'		,      eos_token='(EOS)'							)
													lowercase__      :		List[str]          =     self.get_feature_extractor(do_normalize=snake_case__		,      padding_value=1.0							)

													lowercase__      :		Dict          =     WavaVecaProcessor.from_pretrained(
													    self.tmpdirname		,      bos_token='(BOS)'		,      eos_token='(EOS)'		,      do_normalize=snake_case__		,      padding_value=1.0							)

													self.assertEqual(processor.tokenizer.get_vocab()		,      tokenizer_add_kwargs.get_vocab()							)
													self.assertIsInstance(processor.tokenizer		,      snake_case__							)

													self.assertEqual(processor.feature_extractor.to_json_string()		,      feature_extractor_add_kwargs.to_json_string()							)
													self.assertIsInstance(processor.feature_extractor		,      snake_case__							)


						def 		_UpperCAmelCase	(       self							)	-> List[str]:
													lowercase__      :		List[str]          =     self.get_feature_extractor()
													lowercase__      :		Optional[int]          =     self.get_tokenizer()

													lowercase__      :		Optional[int]          =     WavaVecaProcessor(tokenizer=snake_case__		,      feature_extractor=snake_case__							)

													lowercase__      :		Optional[int]          =     floats_list((3, 1_0_0_0)							)

													lowercase__      :		str          =     feature_extractor(snake_case__		,      return_tensors='np'							)
													lowercase__      :		Optional[Any]          =     processor(snake_case__		,      return_tensors='np'							)

													for key in input_feat_extract.keys():
																				self.assertAlmostEqual(input_feat_extract[key].sum()		,      input_processor[key].sum()		,      delta=1e-2							)


						def 		_UpperCAmelCase	(       self							)	-> Tuple:
													lowercase__      :		List[Any]          =     self.get_feature_extractor()
													lowercase__      :		Union[str, Any]          =     self.get_tokenizer()

													lowercase__      :		Any          =     WavaVecaProcessor(tokenizer=snake_case__		,      feature_extractor=snake_case__							)

													lowercase__      :		Optional[Any]          =     'This is a test string'

													lowercase__      :		Any          =     processor(text=snake_case__							)

													lowercase__      :		Optional[int]          =     tokenizer(snake_case__							)

													for key in encoded_tok.keys():
																				self.assertListEqual(encoded_tok[key]		,      encoded_processor[key]							)


						def 		_UpperCAmelCase	(       self							)	-> Tuple:
													lowercase__      :		Any          =     self.get_feature_extractor()
													lowercase__      :		Optional[Any]          =     self.get_tokenizer()

													lowercase__      :		Optional[int]          =     WavaVecaProcessor(tokenizer=snake_case__		,      feature_extractor=snake_case__							)

													lowercase__      :		List[Any]          =     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

													lowercase__      :		List[Any]          =     processor.batch_decode(snake_case__							)
													lowercase__      :		Tuple          =     tokenizer.batch_decode(snake_case__							)

													self.assertListEqual(snake_case__		,      snake_case__							)


						def 		_UpperCAmelCase	(       self							)	-> Union[str, Any]:
													lowercase__      :		str          =     self.get_feature_extractor()
													lowercase__      :		int          =     self.get_tokenizer()

													lowercase__      :		str          =     WavaVecaProcessor(tokenizer=snake_case__		,      feature_extractor=snake_case__							)

													self.assertListEqual(
													    processor.model_input_names		,      feature_extractor.model_input_names		,      msg='`processor` and `feature_extractor` model input names do not match'		,      )


"""simple docstring"""





import logging
from pathlib import Path
from typing import Any, List, Tuple

import yaml


# loading package files: https://stackoverflow.com/a/20885799
try:
       import importlib.resources as pkg_resources
except ImportError:
       # Try backported to PY<37 `importlib_resources`.
       import importlib_resources as pkg_resources

from . import resources


_UpperCamelCase       :						Optional[int]     =   "https://github.com/huggingface/datasets/tree/main/src/datasets/utils"
_UpperCamelCase       :						Union[str, Any]     =   f'''{BASE_REF_URL}/{__file__}'''
_UpperCamelCase       :						Any     =   logging.getLogger(__name__)





def     a_					(				_lowerCAmelCase  :			str					):





       '''simple docstring'''

       lowercase__      :		Optional[Any]          =     pkg_resources.read_text(_lowerCAmelCase       ,			_lowerCAmelCase					)
       return yaml.safe_load(_lowerCAmelCase					), f"""{BASE_REF_URL}/resources/{resource}"""


_UpperCamelCase   ,				_UpperCamelCase       :						int     =   load_yaml_resource("readme_structure.yaml")

_UpperCamelCase       :						Optional[Any]     =   [
    "[Needs More Information]",
    "[More Information Needed]",
    "(https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)",
]

# Dictionary representation of section/readme, error_list, warning_list
_UpperCamelCase       :						List[Any]     =   Tuple[dict, List[str], List[str]]


class 					UpperCAmelCase_     :


      def __init__(       self		,      a		,      a		,      a = None		,      a = False							)	-> str:
             lowercase__      :		List[str]          =     name
             lowercase__      :		int          =     level
             lowercase__      :		Dict          =     lines
             lowercase__      :		Optional[int]          =     ''
             lowercase__      :		List[str]          =     True
             lowercase__      :		Union[str, Any]          =     {}
             lowercase__      :		Any          =     []
             lowercase__      :		Optional[int]          =     []
             if self.lines is not None:
                    self.parse(suppress_parsing_errors=a							)


      def 		_UpperCAmelCase	(       self		,      a = False							)	-> Any:
             lowercase__      :		List[str]          =     ''
             lowercase__      :		int          =     []
             lowercase__      :		Any          =     False
             for line in self.lines:
                    if line.strip(' \n'							) == "":
                           continue
                    elif line.strip(' \n'							)[:3] == "```":
                           lowercase__      :		Optional[Any]          =     not code_start
                    elif line.split()[0] == self.level + "#" and not code_start:
                           if current_sub_level != "":
                                  lowercase__      :		Tuple          =     Section(a		,      self.level + '#'		,      a							)
                                  lowercase__      :		str          =     []
                           else:
                                  if current_lines != []:
                                         self.text += "".join(a							).strip()
                                         if self.text != "" and self.text not in FILLER_TEXT:
                                                lowercase__      :		List[Any]          =     False
                                         lowercase__      :		List[str]          =     []

                           lowercase__      :		Dict          =     ' '.join(line.split()[1:]							).strip(' \n'							)
                    else:
                           current_lines.append(a							)
             else:
                    if current_sub_level != "":
                           if current_sub_level in self.content:
                                  self.parsing_error_list.append(
                                      f"""Multiple sections with the same heading `{current_sub_level}` have been found. Please keep only one of these sections."""							)
                           lowercase__      :		Tuple          =     Section(a		,      self.level + '#'		,      a							)
                    else:
                           if current_lines != []:
                                  self.text += "".join(a							).strip()
                                  if self.text != "" and self.text not in FILLER_TEXT:
                                         lowercase__      :		Dict          =     False

             if self.level == "" and not suppress_parsing_errors:
                    if self.parsing_error_list != [] or self.parsing_warning_list != []:
                           lowercase__      :		Optional[Any]          =     '\n'.join('-\t' + x for x in self.parsing_error_list + self.parsing_warning_list							)
                           lowercase__      :		int          =     f"""The following issues were found while parsing the README at `{self.name}`:\n""" + errors
                           raise ValueError(a							)


      def 		_UpperCAmelCase	(       self		,      a							)	-> ReadmeValidatorOutput:
             lowercase__      :		Tuple          =     []
             lowercase__      :		int          =     []
             if structure["allow_empty"] is False:
                    # If content is expected
                    if self.is_empty_text and self.content == {}:
                           # If no content is found, mention it in the error_list
                           error_list.append(f"""Expected some content in section `{self.name}` but it is empty."""							)

             if structure["allow_empty_text"] is False:
                    # If some text is expected
                    if self.is_empty_text:
                           # If no text is found, mention it in the error_list
                           error_list.append(
                               f"""Expected some text in section `{self.name}` but it is empty (text in subsections are ignored)."""							)
        # Subsections Validation
             if structure["subsections"] is not None:
                    # If subsections are expected
                    if self.content == {}:
                           # If no subsections are present
                           lowercase__      :		str          =     [subsection['name'] for subsection in structure['subsections']]
                           # Mention the expected values in the error_list
                           error_list.append(
                               f"""Section `{self.name}` expected the following subsections: {", ".join(["`"+x+"`" for x in values]							)}. Found 'None'."""							)
                    else:
                           # If some subsections are present
                           lowercase__      :		Union[str, Any]          =     [subsection['name'] for subsection in structure['subsections']]
                           lowercase__      :		Any          =     False
                           for idx, name in enumerate(a							):
                                  if name not in self.content:
                                         # If the expected subsection is not present
                                         error_list.append(f"""Section `{self.name}` is missing subsection: `{name}`."""							)
                                         lowercase__      :		str          =     True
                                  else:
                                         # If the subsection is present, validate subsection, return the result
                                         # and concat the errors from subsection to section error_list

                                         # Skip sublevel validation if current level is `###`
                                         if self.level == "###":
                                                continue
                                         else:
                                                lowercase__   ,				lowercase__   ,				lowercase__      :		Optional[Any]          =     self.content[name].validate(
                                                    structure['subsections'][idx]							)
                                         error_list += subsec_error_list
                                         warning_list += subsec_warning_list

                           if has_missing_subsections:  # we only allow to have extra subsections if all the other ones are here
                                  for name in self.content:
                                         if name not in structure_names:
                                                # If an extra subsection is present
                                                warning_list.append(
                                                    f"""`{self.name}` has an extra subsection: `{name}`. Skipping further validation checks for this subsection as expected structure is unknown."""							)
             if error_list:
                    # If there are errors, do not return the dictionary as it is invalid
                    return {}, error_list, warning_list
             else:
                    return self.to_dict(), error_list, warning_list


      def 		_UpperCAmelCase	(       self							)	-> dict:
             return {
                 "name": self.name,
                 "text": self.text,
                 "is_empty_text": self.is_empty_text,
                 "subsections": [value.to_dict() for value in self.content.values()],
             }





class 					UpperCAmelCase_     (   _a):  # Level 0


      def __init__(       self		,      a		,      a		,      a = None		,      a = False							)	-> Any:
             super().__init__(name=a		,      level=''							)  # Not using lines here as we need to use a child class parse
             lowercase__      :		List[Any]          =     structure
             lowercase__      :		Dict          =     -2
             lowercase__      :		Union[str, Any]          =     0
             lowercase__      :		Dict          =     lines
             if self.lines is not None:
                    self.parse(suppress_parsing_errors=a							)


      def 		_UpperCAmelCase	(       self							)	-> Tuple:
             if self.structure is None:
                    lowercase__   ,				lowercase__   ,				lowercase__      :		Any          =     self._validate(a							)
             else:
                    lowercase__   ,				lowercase__   ,				lowercase__      :		Dict          =     self._validate(self.structure							)
             if error_list != [] or warning_list != []:
                    lowercase__      :		Optional[Any]          =     '\n'.join(['-\t' + x for x in error_list + warning_list]							)
                    lowercase__      :		Union[str, Any]          =     f"""The following issues were found for the README at `{self.name}`:\n""" + errors
                    raise ValueError(a							)


      @classmethod
      def 		_UpperCAmelCase	(       cls		,      a		,      a = None		,      a = False							)	-> Tuple:
             with open(a		,      encoding='utf-8'							) as f:
                    lowercase__      :		List[Any]          =     f.readlines()
             return cls(a		,      a		,      a		,      suppress_parsing_errors=a							)


      @classmethod
      def 		_UpperCAmelCase	(       cls		,      a		,      a = None		,      a = "root"		,      a = False							)	-> int:
             lowercase__      :		Optional[Any]          =     string.split('\n'							)
             return cls(a		,      a		,      a		,      suppress_parsing_errors=a							)


      def 		_UpperCAmelCase	(       self		,      a = False							)	-> List[Any]:
             # Skip Tags
             lowercase__      :		Tuple          =     0

             for line in self.lines:
                    self.yaml_tags_line_count += 1
                    if line.strip(' \n'							) == "---":
                           self.tag_count += 1
                           if self.tag_count == 2:
                                  break
                    line_count += 1
             if self.tag_count == 2:
                    lowercase__      :		Optional[int]          =     self.lines[line_count + 1 :]  # Get the last + 1 th item.
             else:
                    lowercase__      :		List[str]          =     self.lines[self.tag_count :]
             super().parse(suppress_parsing_errors=a							)


      def __str__(       self							)	-> Any:
             return str(self.to_dict()							)


      def 		_UpperCAmelCase	(       self		,      a							)	-> str:
             lowercase__      :		Any          =     []
             lowercase__      :		Optional[int]          =     []
             if self.yaml_tags_line_count == 0:
                    warning_list.append('Empty YAML markers are present in the README.'							)
             elif self.tag_count == 0:
                    warning_list.append('No YAML markers are present in the README.'							)
             elif self.tag_count == 1:
                    warning_list.append('Only the start of YAML tags present in the README.'							)
             # Check how many first level sections are present.
             lowercase__      :		int          =     len(self.content.keys()							)
             if num_first_level_keys > 1:
                    # If more than one, add to the error list, continue
                    error_list.append(
                        f"""The README has several first-level headings: {", ".join(["`"+x+"`" for x in list(self.content.keys()							)]							)}. Only one heading is expected. Skipping further validation for this README."""							)
             elif num_first_level_keys < 1:
                    # If less than one, append error.
                    error_list.append(
                        'The README has no first-level headings. One heading is expected. Skipping further validation for this README.'							)

             else:
                    # If one exactly
                    lowercase__      :		Dict          =     list(self.content.keys()							)[0]  # Get the key
                    if start_key.startswith('Dataset Card for'							):  # Check correct start
                           # If the starting is correct, validate all the sections
                           lowercase__   ,				lowercase__   ,				lowercase__      :		Any          =     self.content[start_key].validate(
                               readme_structure['subsections'][0]							)
                           error_list += sec_error_list
                           warning_list += sec_warning_list
                    else:
                           # If not found, append error
                           error_list.append(
                               'No first-level heading starting with `Dataset Card for` found in README. Skipping further validation for this README.'							)
             if error_list:
                    # If there are errors, do not return the dictionary as it is invalid
                    return {}, error_list, warning_list
             else:
                    return self.to_dict(), error_list, warning_list


if __name__ == "__main__":
       from argparse import ArgumentParser

       _UpperCamelCase       :						Tuple     =   ArgumentParser(usage="Validate the content (excluding YAML tags) of a README.md file.")
       ap.add_argument("readme_filepath")
       _UpperCamelCase       :						str     =   ap.parse_args()
       _UpperCamelCase       :						Optional[int]     =   Path(args.readme_filepath)
       _UpperCamelCase       :						Dict     =   ReadMe.from_readme(readme_filepath)

