




import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			List[Any]	):


      '''simple docstring'''



      return EnvironmentCommand()

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str	):


      '''simple docstring'''



      return EnvironmentCommand(args.accelerate_config_file	)







class     A(		lowerCamelCase_  ):



 '''simple docstring'''


 @staticmethod
 def 							a__					(							A_   :    Union[str, Any]    )  ->      str:

       """simple docstring"""






       lowerCamelCase_							=       parser.add_parser('env'    )
       download_parser.set_defaults(func=snake_case__    )
       download_parser.add_argument(
           '--accelerate-config_file'		,				default=snake_case__		,				help='The accelerate config file to use for the default values in the launching script.'		,				)
       download_parser.set_defaults(func=snake_case__    )

 def __init__(							self   :    Tuple		,				A_   :    str		,				*A_   :    List[str]    )  ->      Optional[int]:

       """simple docstring"""






       lowerCamelCase_							=       accelerate_config_file

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

       """simple docstring"""






       lowerCamelCase_							=       'not installed'
       if is_safetensors_available():
             import safetensors

             lowerCamelCase_							=       safetensors.__version__
       elif importlib.util.find_spec('safetensors'    ) is not None:
             import safetensors

             lowerCamelCase_							=       f"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'not found'
       if is_accelerate_available():
             import accelerate
             from accelerate.commands.config import default_config_file, load_config_from_file

             lowerCamelCase_							=       accelerate.__version__
             # Get the default from the config file.
             if self._accelerate_config_file is not None or os.path.isfile(snake_case__    ):
                   lowerCamelCase_							=       load_config_from_file(self._accelerate_config_file    ).to_dict()

             lowerCamelCase_							=       (
                 '\n'.join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]    )
                 if isinstance(snake_case__		,				snake_case__    )
                 else f"""\t{accelerate_config}"""
             )

       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'NA'
       if is_torch_available():
             import torch

             lowerCamelCase_							=       torch.__version__
             lowerCamelCase_							=       torch.cuda.is_available()

       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'NA'
       if is_tf_available():
             import tensorflow as tf

             lowerCamelCase_							=       tf.__version__
             try:
                   # deprecated in v2.1
                   lowerCamelCase_							=       tf.test.is_gpu_available()
             except AttributeError:
                   # returns list of devices, convert to bool
                   lowerCamelCase_							=       bool(tf.config.list_physical_devices('GPU'    )    )

       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'not installed'
       lowerCamelCase_							=       'NA'
       if is_flax_available():
             import flax
             import jax
             import jaxlib

             lowerCamelCase_							=       flax.__version__
             lowerCamelCase_							=       jax.__version__
             lowerCamelCase_							=       jaxlib.__version__
             lowerCamelCase_							=       jax.lib.xla_bridge.get_backend().platform

       lowerCamelCase_							=       {
           '`transformers` version': version,
           'Platform': platform.platform(),
           'Python version': platform.python_version(),
           'Huggingface_hub version': huggingface_hub.__version__,
           'Safetensors version': f"""{safetensors_version}""",
           'Accelerate version': f"""{accelerate_version}""",
           'Accelerate config': f"""{accelerate_config_str}""",
           'PyTorch version (GPU?)': f"""{pt_version} ({pt_cuda_available})""",
           'Tensorflow version (GPU?)': f"""{tf_version} ({tf_cuda_available})""",
           'Flax version (CPU?/GPU?/TPU?)': f"""{flax_version} ({jax_backend})""",
           'Jax version': f"""{jax_version}""",
           'JaxLib version': f"""{jaxlib_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 							a__					(							A_   :    Any    )  ->      Any:

       """simple docstring"""






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









from ....configuration_utils import PretrainedConfig
from ....utils import logging


UpperCamelCase__ :   Any						=							logging.get_logger(__name__)

UpperCamelCase__ :   Any						=							{
    '''Visual-Attention-Network/van-base''': (
        '''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
    ),
}







class 				lowerCAmelCase_       (					lowerCamelCase_							):
				__a     :       List[Any]						=     "van"






				def __init__(			self      ,snake_case__=224      ,snake_case__=3      ,snake_case__=[7, 3, 3, 3]      ,snake_case__=[4, 2, 2, 2]      ,snake_case__=[64, 128, 320, 512]      ,snake_case__=[3, 3, 12, 3]      ,snake_case__=[8, 8, 4, 4]      ,snake_case__="gelu"      ,snake_case__=0.02      ,snake_case__=1E-6      ,snake_case__=1E-2      ,snake_case__=0.0      ,snake_case__=0.0      ,**snake_case__      ,):
							super().__init__(**snake_case__ )
							SCREAMING_SNAKE_CASE_   : Tuple					  =      image_size
							SCREAMING_SNAKE_CASE_   : List[str]					  =      num_channels
							SCREAMING_SNAKE_CASE_   : Dict					  =      patch_sizes
							SCREAMING_SNAKE_CASE_   : str					  =      strides
							SCREAMING_SNAKE_CASE_   : str					  =      hidden_sizes
							SCREAMING_SNAKE_CASE_   : str					  =      depths
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      mlp_ratios
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      hidden_act
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      initializer_range
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      layer_norm_eps
							SCREAMING_SNAKE_CASE_   : int					  =      layer_scale_init_value
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      drop_path_rate
							SCREAMING_SNAKE_CASE_   : List[str]					  =      dropout_rate



