





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


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


def        A__						(							SCREAMING_SNAKE_CASE_		) ->  Tuple[Any, str]:
		lowerCamelCase :			List[Any]    		=pkg_resources.read_text(a__				,							a__		)
		return yaml.safe_load(a__		), F"{BASE_REF_URL}/resources/{resource}"


snake_case_,							snake_case_				=      load_yaml_resource('''readme_structure.yaml''')

snake_case_				=      [
    '''[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
snake_case_				=      Tuple[dict, List[str], List[str]]
class 							snake_case_		:







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







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

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

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







		def       __lowercase (		self      ,  __lowercase )					-> Any:
				lowerCamelCase :			Optional[Any]    		=[]
				lowerCamelCase :			Optional[Any]    		=[]
				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
								lowerCamelCase :			Union[str, Any]    		=[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
								lowerCamelCase :			Optional[int]    		=[subsection['''name'''] for subsection in structure['''subsections''']]
								lowerCamelCase :			Optional[Any]    		=False
								for idx, name in enumerate(__UpperCamelCase ):
										if name not in self.content:
												# If the expected subsection is not present
												error_list.append(F"Section `{self.name}` is missing subsection: `{name}`." )
												lowerCamelCase :			Optional[Any]    		=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:
														lowerCamelCase		, lowerCamelCase		, lowerCamelCase :			Tuple    		=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       __lowercase (		self )					-> Optional[int]:
				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 							snake_case_		(      __SCREAMING_SNAKE_CASE):  # Level 0







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







		def       __lowercase (		self )					-> Tuple:


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







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


				with open(__UpperCamelCase      ,  encoding='''utf-8''' ) as f:
						lowerCamelCase :			Optional[Any]    		=f.readlines()
				return cls(__UpperCamelCase      ,  __UpperCamelCase      ,  __UpperCamelCase      ,  suppress_parsing_errors=__UpperCamelCase )







		@classmethod
		def       __lowercase (		cls      ,  __lowercase      ,  __lowercase = None      ,  __lowercase = "root"      ,  __lowercase = False )					-> Dict:
				lowerCamelCase :			Optional[Any]    		=string.split('''\n''' )
				return cls(__UpperCamelCase      ,  __UpperCamelCase      ,  __UpperCamelCase      ,  suppress_parsing_errors=__UpperCamelCase )







		def       __lowercase (		self      ,  __lowercase = False )					-> List[Any]:
				lowerCamelCase :			List[Any]    		=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:
						lowerCamelCase :			Optional[int]    		=self.lines[line_count + 1 :]  # Get the last + 1 th item.
				else:
						lowerCamelCase :			Optional[Any]    		=self.lines[self.tag_count :]
				super().parse(suppress_parsing_errors=__UpperCamelCase )







		def __str__(		self )					-> Optional[int]:
				return str(self.to_dict() )







		def       __lowercase (		self      ,  __lowercase )					-> Dict:
				lowerCamelCase :			List[Any]    		=[]
				lowerCamelCase :			Union[str, Any]    		=[]
				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.
				lowerCamelCase :			Optional[Any]    		=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
						lowerCamelCase :			str    		=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
								lowerCamelCase		, lowerCamelCase		, lowerCamelCase :			List[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

				snake_case_				=      ArgumentParser(usage='''Validate the content (excluding YAML tags) of a README.md file.''')
				ap.add_argument('''readme_filepath''')
				snake_case_				=      ap.parse_args()
				snake_case_				=      Path(args.readme_filepath)
				snake_case_				=      ReadMe.from_readme(readme_filepath)



import argparse

import runhouse as rh
import torch
from nlp_example import training_function

from accelerate.utils import PrepareForLaunch, patch_environment




def 					lowerCamelCase__					(    *a__	:	Optional[Any]  )		->						Optional[Any]:
       UpperCamelCase_											=							torch.cuda.device_count()
       print(f'''Device count: {num_processes}'''  )
       with patch_environment(
           world_size=a__						,   master_addr="""127.0.01"""						,   master_port="""29500"""						,   mixed_precision=args[1].mixed_precision  ):
              UpperCamelCase_											=							PrepareForLaunch(a__						,   distributed_type="""MULTI_GPU"""  )
              torch.multiprocessing.start_processes(a__						,   args=a__						,   nprocs=a__						,   start_method="""spawn"""  )


if __name__ == "__main__":
      # Refer to https://runhouse-docs.readthedocs-hosted.com/en/main/rh_primitives/cluster.html#hardware-setup
      # for cloud access setup instructions (if using on-demand hardware), and for API specifications.

      # on-demand GPU
      # gpu = rh.cluster(name='rh-cluster', instance_type='V100:1', provider='cheapest', use_spot=False)  # single GPU
      _A							=       rh.cluster(name='''rh-cluster''', instance_type='''V100:4''', provider='''cheapest''', use_spot=False)  # multi GPU
      gpu.up_if_not()

      # on-prem GPU
      # gpu = rh.cluster(
      #           ips=["ip_addr"], ssh_creds={ssh_user:"<username>", ssh_private_key:"<key_path>"}, name="rh-cluster"
      #       )

      # Set up remote function
      _A							=       [
          '''pip:./''',
          '''transformers''',
          '''datasets''',
          '''evaluate''',
          '''tqdm''',
          '''scipy''',
          '''scikit-learn''',
          '''tensorboard''',
          '''torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117''',
      ]
      _A							=       rh.function(fn=launch_train, system=gpu, reqs=reqs, name='''train_bert_glue''')

      # Define train args/config, run train function
      _A							=       argparse.Namespace(cpu=False, mixed_precision='''fp16''')
      _A							=       {'''lr''': 2E-5, '''num_epochs''': 3, '''seed''': 42, '''batch_size''': 16}
      launch_train_gpu(config, train_args, stream_logs=True)

      # Alternatively, we can just run as instructed in the README (but only because there's already a wrapper CLI):
      # gpu.install_packages(reqs)
      # gpu.run(['accelerate launch --multi_gpu accelerate/examples/nlp_example.py'])



