





'''simple docstring'''






from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

snake_case_     =	TypeVar("""KEY""")
snake_case_     =	TypeVar("""VAL""")


@dataclass(frozen=a		,					slots=a				)
class   _lowercase						(							Generic[KEY, VAL]				):
   _UpperCamelCase       		=   42
   _UpperCamelCase       		=   42







class   _lowercase						(							_Item				):


   def __init__( self					):
       super().__init__(_UpperCAmelCase    ,   _UpperCAmelCase					)


   def __bool__( self					):
       return False







snake_case_     =	_DeletedItem()


class   _lowercase						(							MutableMapping[KEY, VAL]				):


   def __init__( self    ,   _UpperCAmelCase = 8    ,   _UpperCAmelCase = 0.75					):
       A       :       Dict							=						initial_block_size
       A       :       list[_Item | None]							=						[None] * initial_block_size
       assert 0.0 < capacity_factor < 1.0
       A       :       List[Any]							=						capacity_factor
       A       :       int							=						0


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       return hash(_UpperCAmelCase					) % len(self._buckets					)


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       return (ind + 1) % len(self._buckets					)


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       A       :       Union[str, Any]							=						self._buckets[ind]
       if not stored:
           A       :       List[Any]							=						_Item(_UpperCAmelCase    ,   _UpperCAmelCase					)
           self._len += 1
           return True
       elif stored.key == key:
           A       :       List[str]							=						_Item(_UpperCAmelCase    ,   _UpperCAmelCase					)
           return True
       else:
           return False


   def 					snake_case				( self					):
       A       :       str							=						len(self._buckets					) * self._capacity_factor
       return len(self					) >= int(_UpperCAmelCase					)


   def 					snake_case				( self					):
       if len(self._buckets					) <= self._initial_block_size:
           return False
       A       :       int							=						len(self._buckets					) * self._capacity_factor / 2
       return len(self					) < limit


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       A       :       str							=						self._buckets
       A       :       str							=						[None] * new_size
       A       :       List[Any]							=						0
       for item in old_buckets:
           if item:
               self._add_item(item.key    ,   item.val					)


   def 					snake_case				( self					):
       self._resize(len(self._buckets					) * 2					)


   def 					snake_case				( self					):
       self._resize(len(self._buckets					) // 2					)


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       A       :       Optional[Any]							=						self._get_bucket_index(_UpperCAmelCase					)
       for _ in range(len(self._buckets					)					):
           yield ind
           A       :       Union[str, Any]							=						self._get_next_ind(_UpperCAmelCase					)


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       for ind in self._iterate_buckets(_UpperCAmelCase					):
           if self._try_set(_UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
               break


   def __setitem__( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       if self._is_full():
           self._size_up()

       self._add_item(_UpperCAmelCase    ,   _UpperCAmelCase					)


   def __delitem__( self    ,   _UpperCAmelCase					):
       for ind in self._iterate_buckets(_UpperCAmelCase					):
           A       :       Dict							=						self._buckets[ind]
           if item is None:
               raise KeyError(_UpperCAmelCase					)
           if item is _deleted:
               continue
           if item.key == key:
               A       :       Any							=						_deleted
               self._len -= 1
               break
       if self._is_sparse():
           self._size_down()


   def __getitem__( self    ,   _UpperCAmelCase					):
       for ind in self._iterate_buckets(_UpperCAmelCase					):
           A       :       List[str]							=						self._buckets[ind]
           if item is None:
               break
           if item is _deleted:
               continue
           if item.key == key:
               return item.val
       raise KeyError(_UpperCAmelCase					)


   def __len__( self					):
       return self._len


   def __iter__( self					):
       yield from (item.key for item in self._buckets if item)


   def __repr__( self					):
       A       :       Optional[int]							=						''' ,'''.join(
           f'''{item.key}: {item.val}''' for item in self._buckets if item					)
       return f'''HashMap({val_string})'''










'''simple docstring'''






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 							_lowerCamelCase(  UpperCamelCase__    : Optional[int]		)		->  List[str]:
    return EnvironmentCommand()
def 							_lowerCamelCase(  UpperCamelCase__    : List[Any]		)		->  Tuple:
    return EnvironmentCommand(args.accelerate_config_file		)





class   _lowercase						(							a				):


   @staticmethod
   def 					snake_case				( _UpperCAmelCase					):
       A       :       Optional[Any]							=						parser.add_parser('''env'''					)
       download_parser.set_defaults(func=_UpperCAmelCase					)
       download_parser.add_argument(
           '''--accelerate-config_file'''    ,   default=_UpperCAmelCase    ,   help='''The accelerate config file to use for the default values in the launching script.'''    ,   )
       download_parser.set_defaults(func=_UpperCAmelCase					)


   def __init__( self    ,   _UpperCAmelCase    ,   *_UpperCAmelCase					):
       A       :       Any							=						accelerate_config_file


   def 					snake_case				( self					):
       A       :       Any							=						'''not installed'''
       if is_safetensors_available():
           import safetensors

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

           A       :       int							=						f'''{safetensors.__version__} but is ignored because of PyTorch version too old.'''

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

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

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

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

           A       :       Optional[int]							=						torch.__version__
           A       :       List[Any]							=						torch.cuda.is_available()

       A       :       Dict							=						'''not installed'''
       A       :       Any							=						'''NA'''
       if is_tf_available():
           import tensorflow as tf

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

       A       :       str							=						'''not installed'''
       A       :       Dict							=						'''not installed'''
       A       :       int							=						'''not installed'''
       A       :       Tuple							=						'''NA'''
       if is_flax_available():
           import flax
           import jax
           import jaxlib

           A       :       Any							=						flax.__version__
           A       :       Tuple							=						jax.__version__
           A       :       int							=						jaxlib.__version__
           A       :       List[Any]							=						jax.lib.xla_bridge.get_backend().platform

       A       :       Union[str, Any]							=						{
           '''`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(_UpperCAmelCase					)					)

       return info


   @staticmethod
   def 					snake_case				( _UpperCAmelCase					):
       return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]					) + "\n"
