





from argparse import ArgumentParser

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


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



def    __lowercase   (      _SCREAMING_SNAKE_CASE	) ->   List[Any]:


      '''simple docstring'''


      if not path:
            return "pipe"

      for ext in PipelineDataFormat.SUPPORTED_FORMATS:
            if path.endswith(_SCREAMING_SNAKE_CASE	):
                  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    __lowercase   (      _SCREAMING_SNAKE_CASE	) ->   Tuple:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						pipeline(
          task=args.task ,						model=args.model if args.model else None ,						config=args.config ,						tokenizer=args.tokenizer ,						device=args.device ,						)
      SCREAMING_SNAKE_CASE		=						try_infer_format_from_ext(args.input	) if args.format == """infer""" else args.format
      SCREAMING_SNAKE_CASE		=						PipelineDataFormat.from_str(
          format=_SCREAMING_SNAKE_CASE ,						output_path=args.output ,						input_path=args.input ,						column=args.column if args.column else nlp.default_input_names ,						overwrite=args.overwrite ,						)
      return RunCommand(_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	)



class 		UpperCamelCase__ (      lowerCAmelCase_   ):



     '''simple docstring'''

     def __init__(							self						:    Any						,lowerCamelCase__						:    Pipeline						,lowerCamelCase__						:    PipelineDataFormat       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						nlp
           SCREAMING_SNAKE_CASE		=						reader






     @staticmethod
     def 				SCREAMING_SNAKE_CASE__  (							lowerCamelCase__						:    ArgumentParser       )     ->		Any:




           '''simple docstring'''


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






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE,					SCREAMING_SNAKE_CASE		=						self._nlp, []

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

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









import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402


SCREAMING_SNAKE_CASE_						   =       get_tests_dir("""fixtures/dummy-config.json""")

class 		UpperCamelCase__ (      unittest.TestCase   ):



     '''simple docstring'''

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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						0






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Any       )     ->		str:




           '''simple docstring'''


           self.assertIsNotNone(transformers.models.auto.__spec__       )
           self.assertIsNotNone(importlib.util.find_spec("""transformers.models.auto"""       )       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Union[str, Any]       )     ->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""bert-base-uncased"""       )
           self.assertIsInstance(lowerCamelCase__						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    int       )     ->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__       )
           self.assertIsInstance(lowerCamelCase__						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Union[str, Any]       )     ->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__       )
           self.assertIsInstance(lowerCamelCase__						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Tuple       )     ->		Optional[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AutoConfig.for_model("""roberta"""       )
           self.assertIsInstance(lowerCamelCase__						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    int       )     ->		int:




           '''simple docstring'''


           with tempfile.TemporaryDirectory() as tmp_dir:
                 # This model name contains bert and roberta, but roberta ends up being picked.
                 SCREAMING_SNAKE_CASE		=						os.path.join(lowerCamelCase__						,"""fake-roberta"""       )
                 os.makedirs(lowerCamelCase__						,exist_ok=lowerCamelCase__       )
                 with open(os.path.join(lowerCamelCase__						,"""config.json"""       )						,"""w"""       ) as f:
                       f.write(json.dumps({}       )       )
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__       )
                 self.assertEqual(type(lowerCamelCase__       )						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		str:




           '''simple docstring'''


           try:
                 AutoConfig.register("""custom"""						,lowerCamelCase__       )
                 # Wrong model type will raise an error
                 with self.assertRaises(lowerCamelCase__       ):
                       AutoConfig.register("""model"""						,lowerCamelCase__       )
                 # Trying to register something existing in the Transformers library will raise an error
                 with self.assertRaises(lowerCamelCase__       ):
                       AutoConfig.register("""bert"""						,lowerCamelCase__       )

                 # Now that the config is registered, it can be used as any other config with the auto-API
                 SCREAMING_SNAKE_CASE		=						CustomConfig()
                 with tempfile.TemporaryDirectory() as tmp_dir:
                       config.save_pretrained(lowerCamelCase__       )
                       SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__       )
                       self.assertIsInstance(lowerCamelCase__						,lowerCamelCase__       )

           finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]






     def 				SCREAMING_SNAKE_CASE__  (							self						:    str       )     ->		Dict:




           '''simple docstring'''


           with self.assertRaisesRegex(
               lowerCamelCase__						,"""bert-base is not a local folder and is not a valid model identifier"""       ):
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""bert-base"""       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		str:




           '''simple docstring'''


           with self.assertRaisesRegex(
               lowerCamelCase__						,R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""       ):
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__						,revision="""aaaaaa"""       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Tuple       )     ->		List[Any]:




           '''simple docstring'''


           with self.assertRaisesRegex(
               lowerCamelCase__						,"""hf-internal-testing/no-config-test-repo does not appear to have a file named config.json."""						,):
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/no-config-test-repo"""       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Optional[int]       )     ->		Union[str, Any]:




           '''simple docstring'''


           with self.assertRaises(lowerCamelCase__       ):
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""       )
           # If remote code is disabled, we can't load this config.
           with self.assertRaises(lowerCamelCase__       ):
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""						,trust_remote_code=lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""						,trust_remote_code=lowerCamelCase__       )
           self.assertEqual(config.__class__.__name__						,"""NewModelConfig"""       )

           # Test config can be reloaded.
           with tempfile.TemporaryDirectory() as tmp_dir:
                 config.save_pretrained(lowerCamelCase__       )
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained(lowerCamelCase__						,trust_remote_code=lowerCamelCase__       )
           self.assertEqual(reloaded_config.__class__.__name__						,"""NewModelConfig"""       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		Union[str, Any]:




           '''simple docstring'''


           class 		UpperCamelCase__ (      lowerCAmelCase_   ):



                '''simple docstring'''

                __snake_case    :	Union[str, Any]			=			"new-model"

           try:
                 AutoConfig.register("""new-model"""						,lowerCamelCase__       )
                 # If remote code is not set, the default is to use local
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""       )
                 self.assertEqual(config.__class__.__name__						,"""NewModelConfigLocal"""       )

                 # If remote code is disabled, we load the local one.
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""						,trust_remote_code=lowerCamelCase__       )
                 self.assertEqual(config.__class__.__name__						,"""NewModelConfigLocal"""       )

                 # If remote is enabled, we load from the Hub
                 SCREAMING_SNAKE_CASE		=						AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""						,trust_remote_code=lowerCamelCase__       )
                 self.assertEqual(config.__class__.__name__						,"""NewModelConfig"""       )

           finally:
                 if "new-model" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["new-model"]


