



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)











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)






