code: 
  
  
  
  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
  
  
  lowerCAmelCase__	:  Tuple 		='''https://github.com/huggingface/datasets/tree/main/src/datasets/utils'''
  lowerCAmelCase__	:  Union[str, Any] 		=F'''{BASE_REF_URL}/{__file__}'''
  lowerCAmelCase__	:  Tuple 		=logging.getLogger(__name__)
  
  
  
  
  
  
  def 			__lowercase     (				a__     ):
  							__SCREAMING_SNAKE_CASE								=      pkg_resources.read_text(a__							,     a__     )
  							return yaml.safe_load(a__     ), f"""{BASE_REF_URL}/resources/{resource}"""
  
  
  lowerCAmelCase__	:  Optional[Any] 		=load_yaml_resource('''readme_structure.yaml''')
  
  lowerCAmelCase__	:  Dict 		=[
      '''[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
  lowerCAmelCase__	:  Union[str, Any] 		=Tuple[dict, List[str], List[str]]
  
  class      UpperCAmelCase_						:
  
  						'''simple docstring'''
  
  
  
  
  						def __init__(					self   ,							_A   ,							_A   ,							_A = None   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      name
  													__SCREAMING_SNAKE_CASE								=      level
  													__SCREAMING_SNAKE_CASE								=      lines
  													__SCREAMING_SNAKE_CASE								=      ''
  													__SCREAMING_SNAKE_CASE								=      True
  													__SCREAMING_SNAKE_CASE								=      {}
  													__SCREAMING_SNAKE_CASE								=      []
  													__SCREAMING_SNAKE_CASE								=      []
  													if self.lines is not None:
  																				self.parse(suppress_parsing_errors=_A	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      ''
  													__SCREAMING_SNAKE_CASE								=      []
  													__SCREAMING_SNAKE_CASE								=      False
  													for line in self.lines:
  																				if line.strip(' \n'	) == "":
  																											continue
  																				elif line.strip(' \n'	)[:3] == "```":
  																											__SCREAMING_SNAKE_CASE								=      not code_start
  																				elif line.split()[0] == self.level + "#" and not code_start:
  																											if current_sub_level != "":
  																																		__SCREAMING_SNAKE_CASE								=      Section(_A   ,							self.level + '#'   ,							_A	)
  																																		__SCREAMING_SNAKE_CASE								=      []
  																											else:
  																																		if current_lines != []:
  																																									self.text += "".join(_A	).strip()
  																																									if self.text != "" and self.text not in FILLER_TEXT:
  																																																__SCREAMING_SNAKE_CASE								=      False
  																																									__SCREAMING_SNAKE_CASE								=      []
  
  																											__SCREAMING_SNAKE_CASE								=      ' '.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."""	)
  																											__SCREAMING_SNAKE_CASE								=      Section(_A   ,							self.level + '#'   ,							_A	)
  																				else:
  																											if current_lines != []:
  																																		self.text += "".join(_A	).strip()
  																																		if self.text != "" and self.text not in FILLER_TEXT:
  																																									__SCREAMING_SNAKE_CASE								=      False
  
  													if self.level == "" and not suppress_parsing_errors:
  																				if self.parsing_error_list != [] or self.parsing_warning_list != []:
  																											__SCREAMING_SNAKE_CASE								=      __SCREAMING_SNAKE_CASE								=      '\n'.join('-\t' + x for x in self.parsing_error_list + self.parsing_warning_list	)
  																											__SCREAMING_SNAKE_CASE								=      f"""The following issues were found while parsing the README at `{self.name}`:\n""" + errors
  																											raise ValueError(_A	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      []
  													__SCREAMING_SNAKE_CASE								=      []
  													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
  																											__SCREAMING_SNAKE_CASE								=      [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
  																											__SCREAMING_SNAKE_CASE								=      [subsection['name'] for subsection in structure['subsections']]
  																											__SCREAMING_SNAKE_CASE								=      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}`."""	)
  																																									__SCREAMING_SNAKE_CASE								=      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:
  																																																__SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE								=      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  _A			(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													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_						(     UpperCamelCase_ ):  # Level 0
  
  						'''simple docstring'''
  
  
  
  
  						def __init__(					self   ,							_A   ,							_A   ,							_A = None   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													super().__init__(name=_A   ,							level=''	)  # Not using lines here as we need to use a child class parse
  													__SCREAMING_SNAKE_CASE								=      structure
  													__SCREAMING_SNAKE_CASE								=      -2
  													__SCREAMING_SNAKE_CASE								=      0
  													__SCREAMING_SNAKE_CASE								=      lines
  													if self.lines is not None:
  																				self.parse(suppress_parsing_errors=_A	)
  
  
  
  
  
  
  						def  _A			(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if self.structure is None:
  																				__SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE								=      self._validate(_A	)
  													else:
  																				__SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE								=      self._validate(self.structure	)
  													if error_list != [] or warning_list != []:
  																				__SCREAMING_SNAKE_CASE								=      '\n'.join(['-\t' + x for x in error_list + warning_list]	)
  																				__SCREAMING_SNAKE_CASE								=      f"""The following issues were found for the README at `{self.name}`:\n""" + errors
  																				raise ValueError(_A	)
  
  
  
  
  
  
  						@classmethod
  						def  _A			(					cls   ,							_A   ,							_A = None   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													with open(_A   ,							encoding='utf-8'	) as f:
  																				__SCREAMING_SNAKE_CASE								=      f.readlines()
  													return cls(_A   ,							_A   ,							_A   ,							suppress_parsing_errors=_A	)
  
  
  
  
  
  
  						@classmethod
  						def  _A			(					cls   ,							_A   ,							_A = None   ,							_A = "root"   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      string.split('\n'	)
  													return cls(_A   ,							_A   ,							_A   ,							suppress_parsing_errors=_A	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A = False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      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:
  																				__SCREAMING_SNAKE_CASE								=      self.lines[line_count + 1 :]  # Get the last + 1 th item.
  													else:
  																				__SCREAMING_SNAKE_CASE								=      self.lines[self.tag_count :]
  													super().parse(suppress_parsing_errors=_A	)
  
  
  
  
  
  
  						def __str__(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													return str(self.to_dict()	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      []
  													__SCREAMING_SNAKE_CASE								=      []
  													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.
  													__SCREAMING_SNAKE_CASE								=      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
  																				__SCREAMING_SNAKE_CASE								=      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
  																											__SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE								=      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
  
  			lowerCAmelCase__	:  List[str] 		=ArgumentParser(usage='''Validate the content (excluding YAML tags) of a README.md file.''')
  			ap.add_argument('''readme_filepath''')
  			lowerCAmelCase__	:  Union[str, Any] 		=ap.parse_args()
  			lowerCAmelCase__	:  Any 		=Path(args.readme_filepath)
  			lowerCAmelCase__	:  Optional[int] 		=ReadMe.from_readme(readme_filepath)
  
  
  
  
  
  
  
style_context: 
  
  
  
  import argparse
  import datetime
  import json
  import time
  import warnings
  from logging import getLogger
  from pathlib import Path
  from typing import Dict, List
  
  import torch
  from tqdm import tqdm
  
  from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
  from utils import calculate_bleu, calculate_rouge, chunks, parse_numeric_n_bool_cl_kwargs, use_task_specific_params
  
  
  lowerCAmelCase__	:  Union[str, Any] 		=getLogger(__name__)
  
  
  lowerCAmelCase__	:  Optional[int] 		='''cuda''' if torch.cuda.is_available() else '''cpu'''
  
  
  
  
  
  
  def 			__lowercase     (				a__							,     a__							,     a__							,     a__ = 8							,     a__ = DEFAULT_DEVICE							,     a__=False							,     a__="summarization"							,     a__=None							,     **a__							,     )       ->				Dict:
  							__SCREAMING_SNAKE_CASE								=      Path(a__     ).open('w'							,     encoding='utf-8'     )
  							__SCREAMING_SNAKE_CASE								=      str(a__     )
  							__SCREAMING_SNAKE_CASE								=      AutoModelForSeqaSeqLM.from_pretrained(a__     ).to(a__     )
  							if fpaa:
  														__SCREAMING_SNAKE_CASE								=      model.half()
  
  							__SCREAMING_SNAKE_CASE								=      AutoTokenizer.from_pretrained(a__     )
  							logger.info(f"""Inferred tokenizer type: {tokenizer.__class__}"""     )  # if this is wrong, check config.model_type.
  
  							__SCREAMING_SNAKE_CASE								=      time.time()
  							# update config with task specific params
  							use_task_specific_params(a__							,     a__     )
  							if prefix is None:
  														__SCREAMING_SNAKE_CASE								=      prefix or getattr(model.config							,     'prefix'							,     ''     ) or ''
  							for examples_chunk in tqdm(list(chunks(a__							,     a__     )     )     ):
  														__SCREAMING_SNAKE_CASE								=      [prefix + text for text in examples_chunk]
  														__SCREAMING_SNAKE_CASE								=      tokenizer(a__							,     return_tensors='pt'							,     truncation=a__							,     padding='longest'     ).to(a__     )
  														__SCREAMING_SNAKE_CASE								=      model.generate(
  														    input_ids=batch.input_ids							,     attention_mask=batch.attention_mask							,     **a__							,     )
  														__SCREAMING_SNAKE_CASE								=      tokenizer.batch_decode(a__							,     skip_special_tokens=a__							,     clean_up_tokenization_spaces=a__     )
  														for hypothesis in dec:
  																					fout.write(hypothesis + '\n'     )
  																					fout.flush()
  							fout.close()
  							__SCREAMING_SNAKE_CASE								=      int(time.time() - start_time     )  # seconds
  							__SCREAMING_SNAKE_CASE								=      len(a__     )
  							return {"n_obs": n_obs, "runtime": runtime, "seconds_per_sample": round(runtime / n_obs							,     4     )}
  
  
  
  
  
  
  def 			__lowercase     (				)       ->				Dict:
  							return datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'     )
  
  
  
  
  
  
  def 			__lowercase     (				a__=True     )       ->				Optional[Any]:
  							__SCREAMING_SNAKE_CASE								=      argparse.ArgumentParser()
  							parser.add_argument('model_name'							,     type=a__							,     help='like facebook/bart-large-cnn,t5-base, etc.'     )
  							parser.add_argument('input_path'							,     type=a__							,     help='like cnn_dm/test.source'     )
  							parser.add_argument('save_path'							,     type=a__							,     help='where to save summaries'     )
  							parser.add_argument('--reference_path'							,     type=a__							,     required=a__							,     help='like cnn_dm/test.target'     )
  							parser.add_argument('--score_path'							,     type=a__							,     required=a__							,     default='metrics.json'							,     help='where to save metrics'     )
  							parser.add_argument('--device'							,     type=a__							,     required=a__							,     default=a__							,     help='cuda, cuda:1, cpu etc.'     )
  							parser.add_argument(
  							    '--prefix'							,     type=a__							,     required=a__							,     default=a__							,     help='will be added to the begininng of src examples'     )
  							parser.add_argument('--task'							,     type=a__							,     default='summarization'							,     help='used for task_specific_params + metrics'     )
  							parser.add_argument('--bs'							,     type=a__							,     default=8							,     required=a__							,     help='batch size'     )
  							parser.add_argument(
  							    '--n_obs'							,     type=a__							,     default=-1							,     required=a__							,     help='How many observations. Defaults to all.'     )
  							parser.add_argument('--fp16'							,     action='store_true'     )
  							parser.add_argument('--dump-args'							,     action='store_true'							,     help='print the custom hparams with the results'     )
  							parser.add_argument(
  							    '--info'							,     nargs='?'							,     type=a__							,     const=datetime_now()							,     help=(
  							        'use in conjunction w/ --dump-args to print with the results whatever other info you\'d like, e.g.'
  							        ' lang=en-ru. If no value is passed, the current datetime string will be used.'
  							    )							,     )
  							# Unspecified args like --num_beams=2 --decoder_start_token_id=4 are passed to model.generate
  							__SCREAMING_SNAKE_CASE							, __SCREAMING_SNAKE_CASE								=      parser.parse_known_args()
  							__SCREAMING_SNAKE_CASE								=      parse_numeric_n_bool_cl_kwargs(a__     )
  							if parsed_args and verbose:
  														print(f"""parsed the following generate kwargs: {parsed_args}"""     )
  							with open(args.input_path     ) as f:
  														__SCREAMING_SNAKE_CASE								=      [' ' + x.rstrip() if 't5' in args.model_name else x.rstrip() for x in f.readlines()]
  							if args.n_obs > 0:
  														__SCREAMING_SNAKE_CASE								=      examples[: args.n_obs]
  							Path(args.save_path     ).parent.mkdir(exist_ok=a__     )
  							if args.reference_path is None and Path(args.score_path     ).exists():
  														warnings.warn(f"""score_path {args.score_path} will be overwritten unless you type ctrl-c."""     )
  							__SCREAMING_SNAKE_CASE								=      generate_summaries_or_translations(
  							    a__							,     args.save_path							,     args.model_name							,     batch_size=args.bs							,     device=args.device							,     fpaa=args.fpaa							,     task=args.task							,     prefix=args.prefix							,     **a__							,     )
  
  							if args.reference_path is None:
  														return {}
  
  							# Compute scores
  							__SCREAMING_SNAKE_CASE								=      calculate_bleu if 'translation' in args.task else calculate_rouge
  							__SCREAMING_SNAKE_CASE								=      [x.rstrip() for x in open(args.save_path     ).readlines()]
  							__SCREAMING_SNAKE_CASE								=      [x.rstrip() for x in open(args.reference_path     ).readlines()][: len(a__     )]
  							__SCREAMING_SNAKE_CASE								=      score_fn(a__							,     a__     )
  							scores.update(a__     )
  
  							if args.dump_args:
  														scores.update(a__     )
  							if args.info:
  														__SCREAMING_SNAKE_CASE								=      args.info
  
  							if verbose:
  														print(a__     )
  
  							if args.score_path is not None:
  														json.dump(a__							,     open(args.score_path							,     'w'     )     )
  
  							return scores
  
  
  if __name__ == "__main__":
  			# Usage for MT:
  			# python run_eval.py MODEL_NAME $DATA_DIR/test.source $save_dir/test_translations.txt --reference_path $DATA_DIR/test.target --score_path $save_dir/test_bleu.json  --task translation $@
  			run_generate(verbose=True)
  
  
  
  
  
  
  