
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


lowercase__				:				Any						=      "https://github.com/huggingface/datasets/tree/main/src/datasets/utils"
lowercase__				:				str						=      F"{BASE_REF_URL}/{__file__}"
lowercase__				:				str						=      logging.getLogger(__name__)




def 						A_			(				snake_case				: str			)   ->     Tuple[Any, str]:



						'''simple docstring'''

						__UpperCamelCase  	=      pkg_resources.read_text(snake_case			,   snake_case			)
						return yaml.safe_load(snake_case			), f"{BASE_REF_URL}/resources/{resource}"


lowercase__		,	lowercase__				:				Any						=      load_yaml_resource("readme_structure.yaml")

lowercase__				:				List[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
lowercase__				:				Any						=      Tuple[dict, List[str], List[str]]






class 							SCREAMING_SNAKE_CASE__     :

							"""simple docstring"""






							def __init__(	self  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None  ,						SCREAMING_SNAKE_CASE_ = False      )-> int:





													'''simple docstring'''






													__UpperCamelCase  	=      name
													__UpperCamelCase  	=      level
													__UpperCamelCase  	=      lines
													__UpperCamelCase  	=      ''''''
													__UpperCamelCase  	=      True
													__UpperCamelCase  	=      {}
													__UpperCamelCase  	=      []
													__UpperCamelCase  	=      []
													if self.lines is not None:
																			self.parse(suppress_parsing_errors=SCREAMING_SNAKE_CASE_      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_ = False      )-> Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase  	=      ''''''
													__UpperCamelCase  	=      []
													__UpperCamelCase  	=      False
													for line in self.lines:
																			if line.strip(''' \n'''      ) == "":
																									continue
																			elif line.strip(''' \n'''      )[:3] == "```":
																									__UpperCamelCase  	=      not code_start
																			elif line.split()[0] == self.level + "#" and not code_start:
																									if current_sub_level != "":
																															__UpperCamelCase  	=      Section(SCREAMING_SNAKE_CASE_  ,						self.level + '''#'''  ,						SCREAMING_SNAKE_CASE_      )
																															__UpperCamelCase  	=      []
																									else:
																															if current_lines != []:
																																					self.text += "".join(SCREAMING_SNAKE_CASE_      ).strip()
																																					if self.text != "" and self.text not in FILLER_TEXT:
																																											__UpperCamelCase  	=      False
																																					__UpperCamelCase  	=      []

																									__UpperCamelCase  	=      ''' '''.join(line.split()[1:]      ).strip(''' \n'''      )
																			else:
																									current_lines.append(SCREAMING_SNAKE_CASE_      )
													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."      )
																									__UpperCamelCase  	=      Section(SCREAMING_SNAKE_CASE_  ,						self.level + '''#'''  ,						SCREAMING_SNAKE_CASE_      )
																			else:
																									if current_lines != []:
																															self.text += "".join(SCREAMING_SNAKE_CASE_      ).strip()
																															if self.text != "" and self.text not in FILLER_TEXT:
																																					__UpperCamelCase  	=      False

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



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> ReadmeValidatorOutput:





													'''simple docstring'''






													__UpperCamelCase  	=      []
													__UpperCamelCase  	=      []
													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
																									__UpperCamelCase  	=      [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
																									__UpperCamelCase  	=      [subsection['''name'''] for subsection in structure['''subsections''']]
																									__UpperCamelCase  	=      False
																									for idx, name in enumerate(SCREAMING_SNAKE_CASE_      ):
																															if name not in self.content:
																																					# If the expected subsection is not present
																																					error_list.append(F"Section `{self.name}` is missing subsection: `{name}`."      )
																																					__UpperCamelCase  	=      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:
																																											__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase  	=      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      )-> dict:





													'''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 							SCREAMING_SNAKE_CASE__     (				SCREAMING_SNAKE_CASE_     ):  # Level 0

							"""simple docstring"""






							def __init__(	self  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None  ,						SCREAMING_SNAKE_CASE_ = False      )-> List[str]:





													'''simple docstring'''






													super().__init__(name=SCREAMING_SNAKE_CASE_  ,						level=''''''      )  # Not using lines here as we need to use a child class parse
													__UpperCamelCase  	=      structure
													__UpperCamelCase  	=      -2
													__UpperCamelCase  	=      0
													__UpperCamelCase  	=      lines
													if self.lines is not None:
																			self.parse(suppress_parsing_errors=SCREAMING_SNAKE_CASE_      )



							def      A__		(	self      )-> Optional[Any]:





													'''simple docstring'''






													if self.structure is None:
																			__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase  	=      self._validate(SCREAMING_SNAKE_CASE_      )
													else:
																			__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase  	=      self._validate(self.structure      )
													if error_list != [] or warning_list != []:
																			__UpperCamelCase  	=      '''\n'''.join(['''-\t''' + x for x in error_list + warning_list]      )
																			__UpperCamelCase  	=      F"The following issues were found for the README at `{self.name}`:\n" + errors
																			raise ValueError(SCREAMING_SNAKE_CASE_      )



							@classmethod
							def      A__		(	cls  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None  ,						SCREAMING_SNAKE_CASE_ = False      )-> Union[str, Any]:





													'''simple docstring'''






													with open(SCREAMING_SNAKE_CASE_  ,						encoding='''utf-8'''      ) as f:
																			__UpperCamelCase  	=      f.readlines()
													return cls(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						suppress_parsing_errors=SCREAMING_SNAKE_CASE_      )



							@classmethod
							def      A__		(	cls  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None  ,						SCREAMING_SNAKE_CASE_ = "root"  ,						SCREAMING_SNAKE_CASE_ = False      )-> Tuple:





													'''simple docstring'''






													__UpperCamelCase  	=      string.split('''\n'''      )
													return cls(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						suppress_parsing_errors=SCREAMING_SNAKE_CASE_      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_ = False      )-> Dict:





													'''simple docstring'''






													__UpperCamelCase  	=      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:
																			__UpperCamelCase  	=      self.lines[line_count + 1 :]  # Get the last + 1 th item.
													else:
																			__UpperCamelCase  	=      self.lines[self.tag_count :]
													super().parse(suppress_parsing_errors=SCREAMING_SNAKE_CASE_      )



							def __str__(	self      )-> Optional[Any]:





													'''simple docstring'''






													return str(self.to_dict()      )



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_      )-> Any:





													'''simple docstring'''






													__UpperCamelCase  	=      []
													__UpperCamelCase  	=      []
													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.
													__UpperCamelCase  	=      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
																			__UpperCamelCase  	=      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
																									__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase  	=      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

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





'''simple docstring'''




import logging
from pathlib import Path

import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only

from utils import save_json

def _UpperCamelCase (							SCREAMING_SNAKE_CASE_				):
     lowercase_       :							Optional[Any]  					=       filter(lambda SCREAMING_SNAKE_CASE_				: p.requires_grad	,							model.parameters()				)
     lowercase_       :							Tuple  					=       sum([np.prod(p.size()				) for p in model_parameters]				)
     return params


_A										= logging.getLogger(__name__)


class    UpperCAmelCase__	(							pl.Callback      ):






   """simple docstring"""
   def 		_lowerCamelCase			(self							,					_a							,					_a					)     ->  str:
        lowercase_       :							List[str]  					=       {f'''lr_group_{i}''': param['lr'] for i, param in enumerate(pl_module.trainer.optimizers[0].param_groups					)}
        pl_module.logger.log_metrics(_a					)
   @rank_zero_only
   def 		_lowerCamelCase			(self							,					_a							,					_a							,					_a							,					_a=True					)     ->  None:
        logger.info(f'''***** {type_path} results at step {trainer.global_step:05d} *****'''					)
        lowercase_       :							Union[str, Any]  					=       trainer.callback_metrics
        trainer.logger.log_metrics({k: v for k, v in metrics.items() if k not in ['log', 'progress_bar', 'preds']}					)
        # Log results
        lowercase_       :							Optional[int]  					=       Path(pl_module.hparams.output_dir					)
        if type_path == "test":
             lowercase_       :							Union[str, Any]  					=       od / 'test_results.txt'
             lowercase_       :							Tuple  					=       od / 'test_generations.txt'
        else:
             # this never gets hit. I prefer not to save intermediate generations, and results are in metrics.json
             # If people want this it will be easy enough to add back.
             lowercase_       :							List[str]  					=       od / f'''{type_path}_results/{trainer.global_step:05d}.txt'''
             lowercase_       :							int  					=       od / f'''{type_path}_generations/{trainer.global_step:05d}.txt'''
             results_file.parent.mkdir(exist_ok=_a					)
             generations_file.parent.mkdir(exist_ok=_a					)
        with open(_a							,					'a+'					) as writer:
             for key in sorted(_a					):
                  if key in ["log", "progress_bar", "preds"]:
                       continue
                  lowercase_       :							Any  					=       metrics[key]
                  if isinstance(_a							,					torch.Tensor					):
                       lowercase_       :							Any  					=       val.item()
                  lowercase_       :							List[str]  					=       f'''{key}: {val:.6f}\n'''
                  writer.write(_a					)

        if not save_generations:
             return

        if "preds" in metrics:
             lowercase_       :							Optional[Any]  					=       '\n'.join(metrics['preds']					)
             generations_file.open('w+'					).write(_a					)
   @rank_zero_only
   def 		_lowerCamelCase			(self							,					_a							,					_a					)     ->  Tuple:
        try:
             lowercase_       :							List[Any]  					=       pl_module.model.model.num_parameters()
        except AttributeError:
             lowercase_       :							Dict  					=       pl_module.model.num_parameters()

        lowercase_       :							Optional[Any]  					=       count_trainable_parameters(_a					)
        # mp stands for million parameters
        trainer.logger.log_metrics({'n_params': npars, 'mp': npars / 1e6, 'grad_mp': n_trainable_pars / 1e6}					)
   @rank_zero_only
   def 		_lowerCamelCase			(self							,					_a							,					_a					)     ->  int:
        save_json(pl_module.metrics							,					pl_module.metrics_save_path					)
        return self._write_logs(_a							,					_a							,					'test'					)





   @rank_zero_only
   def 		_lowerCamelCase			(self							,					_a							,					_a					)     ->  List[str]:
        save_json(pl_module.metrics							,					pl_module.metrics_save_path					)
        # Uncommenting this will save val generations
        # return self._write_logs(trainer, pl_module, "valid")



def _UpperCamelCase (							SCREAMING_SNAKE_CASE_	,							SCREAMING_SNAKE_CASE_	,							SCREAMING_SNAKE_CASE_=1	,							SCREAMING_SNAKE_CASE_=False				):
     if metric == "rouge2":
          lowercase_       :							Optional[int]  					=       '{val_avg_rouge2:.4f}-{step_count}'
     elif metric == "bleu":
          lowercase_       :							int  					=       '{val_avg_bleu:.4f}-{step_count}'
     elif metric == "loss":
          lowercase_       :							List[Any]  					=       '{val_avg_loss:.4f}-{step_count}'
     else:
          raise NotImplementedError(
              f'''seq2seq callbacks only support rouge2, bleu and loss, got {metric}, You can make your own by adding to'''
              ' this function.'				)

     lowercase_       :							Tuple  					=       ModelCheckpoint(
         dirpath=SCREAMING_SNAKE_CASE_	,							filename=SCREAMING_SNAKE_CASE_	,							monitor=f'''val_{metric}'''	,							mode='min' if 'loss' in metric else 'max'	,							save_top_k=SCREAMING_SNAKE_CASE_	,							)
     return checkpoint_callback






def _UpperCamelCase (							SCREAMING_SNAKE_CASE_	,							SCREAMING_SNAKE_CASE_				):
     return EarlyStopping(
         monitor=f'''val_{metric}'''	,							mode='min' if 'loss' in metric else 'max'	,							patience=SCREAMING_SNAKE_CASE_	,							verbose=SCREAMING_SNAKE_CASE_	,							)




