



from argparse import ArgumentParser

from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand


lowercase_	       =			logging.get_logger(__name__)  # pylint: disable=invalid-name






def 					__lowerCAmelCase		(  __lowerCamelCase	:    str	)  ->						int:
					if not path:
										return "pipe"

					for ext in PipelineDataFormat.SUPPORTED_FORMATS:
										if path.endswith(__lowerCamelCase	):
															return ext

					raise Exception(
					    f"""Unable to determine file format from file extension {path}. """
					    f"""Please provide the format through --format {PipelineDataFormat.SUPPORTED_FORMATS}"""	)






def 					__lowerCAmelCase		(  __lowerCamelCase	:    int	)  ->						Tuple:
					__lowerCAmelCase	   =pipeline(
					    task=args.task				,   model=args.model if args.model else None				,   config=args.config				,   tokenizer=args.tokenizer				,   device=args.device				,   )
					__lowerCAmelCase	   =try_infer_format_from_ext(args.input	) if args.format == """infer""" else args.format
					__lowerCAmelCase	   =PipelineDataFormat.from_str(
					    format=__lowerCamelCase				,   output_path=args.output				,   input_path=args.input				,   column=args.column if args.column else nlp.default_input_names				,   overwrite=args.overwrite				,   )
					return RunCommand(__lowerCamelCase				,   __lowerCamelCase	)






class 						__a (     SCREAMING_SNAKE_CASE				):



	def __init__(						self							:    Dict				,	snake_case_							:    Pipeline				,	snake_case_							:    PipelineDataFormat)->							List[str]:
						__lowerCAmelCase	   =nlp
						__lowerCAmelCase	   =reader



	@staticmethod
	def 		UpperCamelCase							(						snake_case_							:    ArgumentParser)->							Union[str, Any]:
						__lowerCAmelCase	   =parser.add_parser("""run"""				,	help="""Run a pipeline through the CLI""")
						run_parser.add_argument("""--task"""				,	choices=get_supported_tasks()				,	help="""Task to run""")
						run_parser.add_argument("""--input"""				,	type=snake_case_				,	help="""Path to the file to use for inference""")
						run_parser.add_argument("""--output"""				,	type=snake_case_				,	help="""Path to the file that will be used post to write results.""")
						run_parser.add_argument("""--model"""				,	type=snake_case_				,	help="""Name or path to the model to instantiate.""")
						run_parser.add_argument("""--config"""				,	type=snake_case_				,	help="""Name or path to the model's config to instantiate.""")
						run_parser.add_argument(
						    """--tokenizer"""				,	type=snake_case_				,	help="""Name of the tokenizer to use. (default: same as the model name)""")
						run_parser.add_argument(
						    """--column"""				,	type=snake_case_				,	help="""Name of the column to use as input. (For multi columns input as QA use column1,columns2)"""				,	)
						run_parser.add_argument(
						    """--format"""				,	type=snake_case_				,	default="""infer"""				,	choices=PipelineDataFormat.SUPPORTED_FORMATS				,	help="""Input format to read from"""				,	)
						run_parser.add_argument(
						    """--device"""				,	type=snake_case_				,	default=-1				,	help="""Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"""				,	)
						run_parser.add_argument("""--overwrite"""				,	action="""store_true"""				,	help="""Allow overwriting the output file.""")
						run_parser.set_defaults(func=snake_case_)



	def 		UpperCamelCase							(						self							:    Optional[Any])->							List[str]:
						__lowerCAmelCase   ,	__lowerCAmelCase	   =self._nlp, []

						for entry in self._reader:
											__lowerCAmelCase	   =nlp(**snake_case_) if self._reader.is_multi_columns else nlp(snake_case_)
											if isinstance(snake_case_				,	snake_case_):
																outputs.append(snake_case_)
											else:
																outputs += output

        # Saving data
						if self._nlp.binary_output:
											__lowerCAmelCase	   =self._reader.save_binary(snake_case_)
											logger.warning(F"""Current pipeline requires output to be in binary format, saving at {binary_path}""")
						else:
											self._reader.save(snake_case_)









def 					__lowerCAmelCase		(  __lowerCamelCase	:    int	)  ->						list:
					__lowerCAmelCase	   =int(__lowerCamelCase	)
					if n_element < 1:
										__lowerCAmelCase	   =ValueError("""a should be a positive number"""	)
										raise my_error

					__lowerCAmelCase	   =[1]
					__lowerCAmelCase   ,	__lowerCAmelCase   ,	__lowerCAmelCase	   =(0, 0, 0)
					__lowerCAmelCase	   =1
					while index < n_element:
										while hamming_list[i] * 2 <= hamming_list[-1]:
															i += 1
										while hamming_list[j] * 3 <= hamming_list[-1]:
															j += 1
										while hamming_list[k] * 5 <= hamming_list[-1]:
															k += 1
										hamming_list.append(
										    min(hamming_list[i] * 2				,   hamming_list[j] * 3				,   hamming_list[k] * 5	)	)
										index += 1
					return hamming_list


if __name__ == "__main__":
				lowercase_	       =			input('''Enter the last number (nth term) of the Hamming Number Series: ''')
				print('''Formula of Hamming Number Series => 2^i * 3^j * 5^k''')
				lowercase_	       =			hamming(int(n))
				print('''-----------------------------------------------------''')
				print(F"The list with nth numbers is: {hamming_numbers}")
				print('''-----------------------------------------------------''')




