import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate






@dataclass(frozen=UpperCamelCase_     )
class 		_lowerCamelCase		( UpperCamelCase_     ):
    # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
    __a						=   field(default="text-classification"     ,  metadata={"include_in_asdict_even_if_is_default": True}     )
    __a						=   Features({"text": Value("string"     )}     )
    __a						=   Features({"labels": ClassLabel}     )
    __a						=   "text"
    __a						=   "labels"
    def     UpperCamelCase_					(	self			,			lowerCAmelCase )							->       Tuple:
     if self.label_column not in features:
      raise ValueError(f'Column {self.label_column} is not present in features.' )
     if not isinstance(features[self.label_column]			,			lowerCAmelCase ):
      raise ValueError(f'Column {self.label_column} is not a ClassLabel.' )
     SCREAMING_SNAKE_CASE__: Union[str, Any]=   copy.deepcopy(self )
     SCREAMING_SNAKE_CASE__: Tuple=   self.label_schema.copy()
     SCREAMING_SNAKE_CASE__: Union[str, Any]=   features[self.label_column]
     SCREAMING_SNAKE_CASE__: List[str]=   label_schema
     return task_template



    @property
    def     UpperCamelCase_					(	self )							->       Dict[str, str]:
     return {
         self.text_column: "text",
         self.label_column: "labels",
     }








"""simple docstring"""





import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


__A											=						"""sshleifer/bart-tiny-random"""
__A											=						"""patrickvonplaten/t5-tiny-random"""






@require_torch
class    _lowerCAmelCase  (	unittest.TestCase			):
       """simple docstring"""




       @cached_property
       def 	snake_case		(       self ):



         '''simple docstring'''

         return AutoConfig.from_pretrained(__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :List[str]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=1 )
         self.assertEqual(student.config.num_hidden_layers       ,					1 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :Optional[int]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :List[Any]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=__UpperCAmelCase )
         self.assertEqual(student.config.encoder_layers       ,					1 )
         self.assertEqual(student.config.decoder_layers       ,					self.teacher_config.encoder_layers )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :Optional[int]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=1 )
         self.assertEqual(student.config.encoder_layers       ,					1 )
         self.assertEqual(student.config.decoder_layers       ,					1 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         with self.assertRaises(__UpperCAmelCase ):
           create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=__UpperCAmelCase       ,					d=__UpperCAmelCase )
