



import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


if TYPE_CHECKING:
				import sqlitea

				import sqlalchemy


__A       =datasets.utils.logging.get_logger(__name__)

@dataclass
class 						UpperCAmelCase__     (     datasets.BuilderConfig  ):




			'''simple docstring'''






			UpperCamelCase     		=			None
			UpperCamelCase     		=			None
			UpperCamelCase     		=			None
			UpperCamelCase     		=			True
			UpperCamelCase     		=			None
			UpperCamelCase     		=			None
			UpperCamelCase     		=			None
			UpperCamelCase     		=			1_0000
			UpperCamelCase     		=			None




			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					if self.sql is None:
							raise ValueError('''sql must be specified'''					)
					if self.con is None:
							raise ValueError('''con must be specified'''					)




			def 					snake_case__	(  self				:					Optional[Any]			,			a_				:					dict			,			a_				:					Optional[datasets.Features] = None			,			):
					'''simple docstring'''





					__UpperCAmelCase       :	int						=      config_kwargs.copy()
					# We need to stringify the Selectable object to make its hash deterministic

					# The process of stringifying is explained here: http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html
					__UpperCAmelCase       :	List[Any]						=      config_kwargs['''sql''']
					if not isinstance(a_			,			a_					):
							if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
									import sqlalchemy

									if isinstance(a_			,			sqlalchemy.sql.Selectable					):
											__UpperCAmelCase       :	Union[str, Any]						=      sqlalchemy.create_engine(config_kwargs['''con'''].split('''://'''					)[0] + '''://'''					)
											__UpperCAmelCase       :	List[str]						=      str(sql.compile(dialect=engine.dialect					)					)
											__UpperCAmelCase       :	List[str]						=      sql_str
									else:
											raise TypeError(
											    F'Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(a_					)}: {sql}'					)
							else:
									raise TypeError(
									    F'Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(a_					)}: {sql}'					)
					__UpperCAmelCase       :	List[str]						=      config_kwargs['''con''']
					if not isinstance(a_			,			a_					):
							__UpperCAmelCase       :	Any						=      id(a_					)
							logger.info(
							    F'SQL connection \'con\' of type {type(a_					)} couldn\'t be hashed properly. To enable hashing, specify \'con\' as URI string instead.'					)

					return super().create_config_id(a_			,			custom_features=a_					)




			@property
			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	Dict						=      {
					    '''index_col''': self.index_col,
					    '''columns''': self.columns,
					    '''params''': self.params,
					    '''coerce_float''': self.coerce_float,
					    '''parse_dates''': self.parse_dates,
					}
					return pd_read_sql_kwargs

class 						UpperCAmelCase__     (     datasets.ArrowBasedBuilder  ):




			'''simple docstring'''






			UpperCamelCase     		=			SqlConfig




			def 					snake_case__	(  self				:					List[str]					):
					'''simple docstring'''





					return datasets.DatasetInfo(features=self.config.features					)




			def 					snake_case__	(  self				:					Optional[Any]			,			a_				:					Optional[Any]					):
					'''simple docstring'''





					return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,			gen_kwargs={}					)]




			def 					snake_case__	(  self				:					Union[str, Any]			,			a_				:					pa.Table					):
					'''simple docstring'''





					if self.config.features is not None:
							__UpperCAmelCase       :	str						=      self.config.features.arrow_schema
							if all(not require_storage_cast(a_					) for feature in self.config.features.values()					):
									# cheaper cast
									__UpperCAmelCase       :	List[str]						=      pa.Table.from_arrays([pa_table[field.name] for field in schema]			,			schema=a_					)
							else:
									# more expensive cast; allows str <-> int/float or str to Audio for example
									__UpperCAmelCase       :	List[Any]						=      table_cast(a_			,			a_					)
					return pa_table




			def 					snake_case__	(  self				:					Optional[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	Union[str, Any]						=      self.config.chunksize
					__UpperCAmelCase       :	Tuple						=      pd.read_sql(
					    self.config.sql			,			self.config.con			,			chunksize=a_			,			**self.config.pd_read_sql_kwargs					)
					__UpperCAmelCase       :	List[str]						=      [sql_reader] if chunksize is None else sql_reader
					for chunk_idx, df in enumerate(a_					):
							__UpperCAmelCase       :	List[Any]						=      pa.Table.from_pandas(a_					)
							yield chunk_idx, self._cast_table(a_					)










import json
import logging
import os
import subprocess
from argparse import ArgumentParser


__A       =logging.getLogger(__name__)

def 			a		( ):







		'''simple docstring'''





		__UpperCAmelCase       :	Dict						=      ArgumentParser()
		__UpperCAmelCase				,   __UpperCAmelCase       :	int						=      parser.parse_known_args()
		for arg in unknown:
				if arg.startswith(('''-''', '''--''')		):
						parser.add_argument(arg.split('''='''		)[0]		)

		return parser.parse_args()

def 			a		( ):







		'''simple docstring'''





		__UpperCAmelCase       :	List[Any]						=      parse_args()
		__UpperCAmelCase       :	Tuple						=      88_88
		__UpperCAmelCase       :	Any						=      int(os.environ['''SM_NUM_GPUS''']		)
		__UpperCAmelCase       :	Optional[int]						=      json.loads(os.environ['''SM_HOSTS''']		)
		__UpperCAmelCase       :	int						=      len(_UpperCAmelCase		)
		__UpperCAmelCase       :	Optional[Any]						=      os.environ['''SM_CURRENT_HOST''']
		__UpperCAmelCase       :	List[str]						=      hosts.index(_UpperCAmelCase		)
		__UpperCAmelCase       :	Dict						=      '''INFO'''

		if num_nodes > 1:
				__UpperCAmelCase       :	Tuple						=      f'python -m torch.distributed.launch \\n                --nnodes={num_nodes}  \\n                --node_rank={rank}  \\n                --nproc_per_node={num_gpus}  \\n                --master_addr={hosts[0]}  \\n                --master_port={port} \\n                ./run_glue.py \\n                {"".join(["nested fstring" for parameter,value in args.__dict__.items()]		)}'
		else:
				__UpperCAmelCase       :	Dict						=      f'python -m torch.distributed.launch \\n            --nproc_per_node={num_gpus}  \\n            ./run_glue.py \\n            {"".join(["nested fstring" for parameter,value in args.__dict__.items()]		)}'
		try:
				subprocess.run(_UpperCAmelCase					,  shell=_UpperCAmelCase		)
		except Exception as e:
				logger.info(_UpperCAmelCase		)


if __name__ == "__main__":
				main()





