

"""simple docstring"""




import os
import re
import shutil
import sys
import tempfile
import unittest

import black


__UpperCAmelCase			=					os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
__UpperCAmelCase			=					'    \"""\n    Output class for the scheduler\'s step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"""\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n'







class   __lowercase      (     unittest.TestCase       ):

  def  __lowercase							(	self		:      str     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Optional[Any]        =       tempfile.mkdtemp()
   os.makedirs(os.path.join(self.diffusers_dir       ,"""schedulers/"""     )     )
   UpperCAmelCase__       :	Optional[Any]        =       self.diffusers_dir
   shutil.copy(
       os.path.join(A       ,"""src/diffusers/schedulers/scheduling_ddpm.py"""     )       ,os.path.join(self.diffusers_dir       ,"""schedulers/scheduling_ddpm.py"""     )       ,)

  def  __lowercase							(	self		:      List[str]     ):






   '''simple docstring'''
   UpperCAmelCase__       :	List[Any]        =       """src/diffusers"""
   shutil.rmtree(self.diffusers_dir     )

  def  __lowercase							(	self		:      List[str]       ,A		:      Dict       ,A		:      List[Any]       ,A		:      int       ,A		:      Tuple=None     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Dict        =       comment + f"\nclass {class_name}(nn.Module):\n" + class_code
   if overwrite_result is not None:
    UpperCAmelCase__       :	str        =       comment + f"\nclass {class_name}(nn.Module):\n" + overwrite_result
   UpperCAmelCase__       :	Tuple        =       black.Mode(target_versions={black.TargetVersion.PYaa}       ,line_length=119     )
   UpperCAmelCase__       :	List[str]        =       black.format_str(A       ,mode=A     )
   UpperCAmelCase__       :	List[str]        =       os.path.join(self.diffusers_dir       ,"""new_code.py"""     )
   with open(A       ,"""w"""       ,newline="""\n"""     ) as f:
    f.write(A     )
   if overwrite_result is None:
    self.assertTrue(len(check_copies.is_copy_consistent(A     )     ) == 0     )
   else:
    check_copies.is_copy_consistent(f.name       ,overwrite=A     )
    with open(A       ,"""r"""     ) as f:
     self.assertTrue(f.read()       ,A     )

  def  __lowercase							(	self		:      int     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Dict        =       check_copies.find_code_in_diffusers("""schedulers.scheduling_ddpm.DDPMSchedulerOutput"""     )
   self.assertEqual(A       ,A     )




  def  __lowercase							(	self		:      Optional[Any]     ):






   '''simple docstring'''
   # Base copy consistency
   self.check_copy_consistency(
       """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"""       ,"""DDPMSchedulerOutput"""       ,REFERENCE_CODE + """\n"""       ,)

   # With no empty line at the end
   self.check_copy_consistency(
       """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"""       ,"""DDPMSchedulerOutput"""       ,A       ,)

   # Copy consistency with rename
   self.check_copy_consistency(
       """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"""       ,"""TestSchedulerOutput"""       ,re.sub("""DDPM"""       ,"""Test"""       ,A     )       ,)

   # Copy consistency with a really long name
   UpperCAmelCase__       :	Optional[Any]        =       """TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason"""
   self.check_copy_consistency(
       f"# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}"       ,f"{long_class_name}SchedulerOutput"       ,re.sub("""Bert"""       ,A       ,A     )       ,)

   # Copy consistency with overwrite
   self.check_copy_consistency(
       """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"""       ,"""TestSchedulerOutput"""       ,A       ,overwrite_result=re.sub("""DDPM"""       ,"""Test"""       ,A     )       ,)









'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__  			=				logging.get_logger(__name__)

UpperCAmelCase__  			=				{
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}
class 						a__					(					a_   ):





			'''simple docstring'''

			A						:				Union[str, Any]					      =			'''roberta'''
			def __init__(  self							:			Any			,    lowerCAmelCase_							:			int=50_265			,    lowerCAmelCase_							:			int=768			,    lowerCAmelCase_							:			Optional[Any]=12			,    lowerCAmelCase_							:			Tuple=12			,    lowerCAmelCase_							:			Optional[int]=3_072			,    lowerCAmelCase_							:			List[str]="gelu"			,    lowerCAmelCase_							:			List[str]=0.1			,    lowerCAmelCase_							:			Tuple=0.1			,    lowerCAmelCase_							:			List[Any]=512			,    lowerCAmelCase_							:			Union[str, Any]=2			,    lowerCAmelCase_							:			List[Any]=0.02			,    lowerCAmelCase_							:			Optional[int]=1E-12			,    lowerCAmelCase_							:			str=1			,    lowerCAmelCase_							:			Dict=0			,    lowerCAmelCase_							:			Any=2			,    lowerCAmelCase_							:			List[str]="absolute"			,    lowerCAmelCase_							:			Any=True			,    lowerCAmelCase_							:			Dict=None			,    **lowerCAmelCase_							:			Any			,    )      ->		int:
						super().__init__(pad_token_id=lowerCAmelCase_			,    bos_token_id=lowerCAmelCase_			,    eos_token_id=lowerCAmelCase_			,    **lowerCAmelCase_	)

						__A=	vocab_size
						__A=	hidden_size
						__A=	num_hidden_layers
						__A=	num_attention_heads
						__A=	hidden_act
						__A=	intermediate_size
						__A=	hidden_dropout_prob
						__A=	attention_probs_dropout_prob
						__A=	max_position_embeddings
						__A=	type_vocab_size
						__A=	initializer_range
						__A=	layer_norm_eps
						__A=	position_embedding_type
						__A=	use_cache
						__A=	classifier_dropout


class 						a__					(					a_   ):





			'''simple docstring'''

			@property
			def 					lowerCAmelCase     (  self							:			Any	)      ->		Mapping[str, Mapping[int, str]]:
						if self.task == "multiple-choice":
									__A=	{0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
									__A=	{0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						    ]	)



