'''simple docstring'''


import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     return EnvironmentCommand()






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  @staticmethod
  def _UpperCamelCase					(			snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Tuple       =				parser.add_parser('env'						)
       download_parser.set_defaults(func=snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[int]       =				huggingface_hub.__version__

       UpperCAmelCase_							:       Union[str, Any]       =				'not installed'
       UpperCAmelCase_							:       Optional[Any]       =				'NA'
       if is_torch_available():
            import torch

            UpperCAmelCase_							:       List[str]       =				torch.__version__
            UpperCAmelCase_							:       Dict       =				torch.cuda.is_available()

       UpperCAmelCase_							:       List[str]       =				'not installed'
       if is_transformers_available():
            import transformers

            UpperCAmelCase_							:       List[Any]       =				transformers.__version__

       UpperCAmelCase_							:       Tuple       =				'not installed'
       if is_accelerate_available():
            import accelerate

            UpperCAmelCase_							:       Tuple       =				accelerate.__version__

       UpperCAmelCase_							:       Optional[int]       =				'not installed'
       if is_xformers_available():
            import xformers

            UpperCAmelCase_							:       str       =				xformers.__version__

       UpperCAmelCase_							:       Dict       =				{
           '`diffusers` version': version,
           'Platform': platform.platform(),
           'Python version': platform.python_version(),
           'PyTorch version (GPU?)': F'''{pt_version} ({pt_cuda_available})''',
           'Huggingface_hub version': hub_version,
           'Transformers version': transformers_version,
           'Accelerate version': accelerate_version,
           'xFormers version': xformers_version,
           'Using GPU in script?': '<fill in>',
           'Using distributed or parallel set-up in script?': '<fill in>',
       }

       print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'						)
       print(self.format_dict(snake_case_						)						)

       return info






  @staticmethod
  def _UpperCamelCase					(			snake_case_						):




       '''simple docstring'''

       return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]						) + "\n"







'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


snake_case__					:      Dict				      =  {
    '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
    '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/config.json''',
    '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/config.json''',
    '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json''',
    '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/config.json''',
    '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/config.json''',
    '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/config.json''',
    '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json''',
}






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  lowerCamelCase_		:str						   =		'''albert'''


  def __init__(			self				,		snake_case_=3_0_0_0_0				,		snake_case_=1_2_8				,		snake_case_=4_0_9_6				,		snake_case_=1_2				,		snake_case_=1				,		snake_case_=6_4				,		snake_case_=1_6_3_8_4				,		snake_case_=1				,		snake_case_="gelu_new"				,		snake_case_=0				,		snake_case_=0				,		snake_case_=5_1_2				,		snake_case_=2				,		snake_case_=0.02				,		snake_case_=1E-12				,		snake_case_=0.1				,		snake_case_="absolute"				,		snake_case_=0				,		snake_case_=2				,		snake_case_=3				,		**snake_case_				,		):




       '''simple docstring'''

       super().__init__(pad_token_id=snake_case_				,		bos_token_id=snake_case_				,		eos_token_id=snake_case_				,		**snake_case_						)

       UpperCAmelCase_							:       List[Any]       =				vocab_size
       UpperCAmelCase_							:       Dict       =				embedding_size
       UpperCAmelCase_							:       str       =				hidden_size
       UpperCAmelCase_							:       Any       =				num_hidden_layers
       UpperCAmelCase_							:       Union[str, Any]       =				num_hidden_groups
       UpperCAmelCase_							:       List[str]       =				num_attention_heads
       UpperCAmelCase_							:       Any       =				inner_group_num
       UpperCAmelCase_							:       Optional[int]       =				hidden_act
       UpperCAmelCase_							:       Tuple       =				intermediate_size
       UpperCAmelCase_							:       Any       =				hidden_dropout_prob
       UpperCAmelCase_							:       List[str]       =				attention_probs_dropout_prob
       UpperCAmelCase_							:       Union[str, Any]       =				max_position_embeddings
       UpperCAmelCase_							:       Dict       =				type_vocab_size
       UpperCAmelCase_							:       Union[str, Any]       =				initializer_range
       UpperCAmelCase_							:       Optional[Any]       =				layer_norm_eps
       UpperCAmelCase_							:       Dict       =				classifier_dropout_prob
       UpperCAmelCase_							:       Tuple       =				position_embedding_type







class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       if self.task == "multiple-choice":
            UpperCAmelCase_							:       Optional[Any]       =				{0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
            UpperCAmelCase_							:       List[Any]       =				{0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
               ('token_type_ids', dynamic_axis),
           ]						)






