

from argparse import ArgumentParser

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


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





def a(lowercase__						):





	'''simple docstring'''
	if not path:
		return "pipe"

	for ext in PipelineDataFormat.SUPPORTED_FORMATS:
		if path.endswith(lowercase__						):
			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 a(lowercase__						):





	'''simple docstring'''
	snake_case_   		=			pipeline(
	    task=args.task      ,			model=args.model if args.model else None      ,			config=args.config      ,			tokenizer=args.tokenizer      ,			device=args.device      ,			)
	snake_case_   		=			try_infer_format_from_ext(args.input						) if args.format == 'infer' else args.format
	snake_case_   		=			PipelineDataFormat.from_str(
	    format=lowercase__      ,			output_path=args.output      ,			input_path=args.input      ,			column=args.column if args.column else nlp.default_input_names      ,			overwrite=args.overwrite      ,			)
	return RunCommand(lowercase__      ,			lowercase__						)






class SCREAMING_SNAKE_CASE	(		__snake_case				):






			"""simple docstring"""




			def __init__(     self			,					__UpperCamelCase			,					__UpperCamelCase				):

				"""simple docstring"""


				snake_case_   		=			nlp
				snake_case_   		=			reader


			@staticmethod
			def       __lowerCAmelCase			(     __UpperCamelCase				):

				"""simple docstring"""


				snake_case_   		=			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=__UpperCamelCase			,					help='Path to the file to use for inference'				)
				run_parser.add_argument('--output'			,					type=__UpperCamelCase			,					help='Path to the file that will be used post to write results.'				)
				run_parser.add_argument('--model'			,					type=__UpperCamelCase			,					help='Name or path to the model to instantiate.'				)
				run_parser.add_argument('--config'			,					type=__UpperCamelCase			,					help='Name or path to the model\'s config to instantiate.'				)
				run_parser.add_argument(
				    '--tokenizer'			,					type=__UpperCamelCase			,					help='Name of the tokenizer to use. (default: same as the model name)'				)
				run_parser.add_argument(
				    '--column'			,					type=__UpperCamelCase			,					help='Name of the column to use as input. (For multi columns input as QA use column1,columns2)'			,					)
				run_parser.add_argument(
				    '--format'			,					type=__UpperCamelCase			,					default='infer'			,					choices=PipelineDataFormat.SUPPORTED_FORMATS			,					help='Input format to read from'			,					)
				run_parser.add_argument(
				    '--device'			,					type=__UpperCamelCase			,					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=__UpperCamelCase				)







			def       __lowerCAmelCase			(     self				):

				"""simple docstring"""


				snake_case_		,							snake_case_   		=			self._nlp, []

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

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



from ..utils import DummyObject, requires_backends


class SCREAMING_SNAKE_CASE	(		metaclass=__snake_case				):






			"""simple docstring"""




			__A    	=	["""flax""", """transformers"""]


			def __init__(     self			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(self			,					['flax', 'transformers']				)


			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







class SCREAMING_SNAKE_CASE	(		metaclass=__snake_case				):






			"""simple docstring"""




			__A    	=	["""flax""", """transformers"""]


			def __init__(     self			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(self			,					['flax', 'transformers']				)


			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







class SCREAMING_SNAKE_CASE	(		metaclass=__snake_case				):






			"""simple docstring"""




			__A    	=	["""flax""", """transformers"""]


			def __init__(     self			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(self			,					['flax', 'transformers']				)


			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







class SCREAMING_SNAKE_CASE	(		metaclass=__snake_case				):






			"""simple docstring"""




			__A    	=	["""flax""", """transformers"""]


			def __init__(     self			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(self			,					['flax', 'transformers']				)


			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)







			@classmethod
			def       __lowerCAmelCase			(     cls			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				requires_backends(cls			,					['flax', 'transformers']				)
