


'''simple docstring'''






# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available





def lowerCamelCase__      (						__lowerCamelCase	:							int=None							):







   '''simple docstring'''




   if subparsers is not None:
      _UpperCAmelCase       :       List[Any]							   =subparsers.add_parser('env'							)
   else:
      _UpperCAmelCase       :       List[Any]							   =argparse.ArgumentParser('Accelerate env command'							)

   parser.add_argument(
       '--config_file'	,   default=__lowerCamelCase	,   help='The config file to use for the default values in the launching script.'							)

   if subparsers is not None:
      parser.set_defaults(func=__lowerCamelCase							)
   return parser





def lowerCamelCase__      (						__lowerCamelCase	:							List[str]							):







   '''simple docstring'''




   _UpperCAmelCase       :       List[str]							   =torch.__version__
   _UpperCAmelCase       :       Union[str, Any]							   =torch.cuda.is_available()
   _UpperCAmelCase       :       Optional[int]							   =is_xpu_available()
   _UpperCAmelCase       :       Union[str, Any]							   =is_npu_available()

   _UpperCAmelCase       :       List[str]							   ='Not found'
   # Get the default from the config file.
   if args.config_file is not None or os.path.isfile(__lowerCamelCase							):
      _UpperCAmelCase       :       Tuple							   =load_config_from_file(args.config_file							).to_dict()

   _UpperCAmelCase       :       int							   ={
       '`Accelerate` version': version,
       'Platform': platform.platform(),
       'Python version': platform.python_version(),
       'Numpy version': np.__version__,
       'PyTorch version (GPU?)': f"{pt_version} ({pt_cuda_available})",
       'PyTorch XPU available': str(__lowerCamelCase							),
       'PyTorch NPU available': str(__lowerCamelCase							),
       'System RAM': f"{psutil.virtual_memory().total / 1_0_2_4 ** 3:.2f} GB",
   }
   if pt_cuda_available:
      _UpperCAmelCase       :       Union[str, Any]							   =torch.cuda.get_device_name()

   print('\nCopy-and-paste the text below in your GitHub issue\n'							)
   print('\n'.join([f"- {prop}: {val}" for prop, val in info.items()]							)							)

   print('- `Accelerate` default config:' if args.config_file is None else '- `Accelerate` config passed:'							)
   _UpperCAmelCase       :       str							   =(
       '\n'.join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()]							)
       if isinstance(__lowerCamelCase	,   __lowerCamelCase							)
       else f"\t{accelerate_config}"
   )
   print(__lowerCamelCase							)

   _UpperCAmelCase       :       str							   =accelerate_config

   return info





def lowerCamelCase__      (						):







   '''simple docstring'''




   _UpperCAmelCase       :       Tuple							   =env_command_parser()
   _UpperCAmelCase       :       int							   =parser.parse_args()
   env_command(__lowerCamelCase							)
   return 0


if __name__ == "__main__":
 raise SystemExit(main())





'''simple docstring'''






from typing import Any





def lowerCamelCase__      (						__lowerCamelCase	:							list	,   __lowerCamelCase	:							list	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   ):







   '''simple docstring'''




   _validation(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   # Creates data structures and fill initial step
   _UpperCAmelCase       :       dict							   ={}
   _UpperCAmelCase       :       dict							   ={}
   for state in states_space:
      _UpperCAmelCase       :       int							   =observations_space[0]
      _UpperCAmelCase       :       int							   =(
          initial_probabilities[state] * emission_probabilities[state][observation]
      )
      _UpperCAmelCase       :       int							   =None

   # Fills the data structure with the probabilities of
   # different transitions and pointers to previous states
   for o in range(1	,   len(__lowerCamelCase							)							):
      _UpperCAmelCase       :       List[Any]							   =observations_space[o]
      _UpperCAmelCase       :       Optional[int]							   =observations_space[o - 1]
      for state in states_space:
         # Calculates the argmax for probability function
         _UpperCAmelCase       :       List[str]							   =''
         _UpperCAmelCase       :       Dict							   =-1
         for k_state in states_space:
            _UpperCAmelCase       :       List[str]							   =(
                probabilities[(k_state, prior_observation)]
                * transition_probabilities[k_state][state]
                * emission_probabilities[state][observation]
            )
            if probability > max_probability:
               _UpperCAmelCase       :       int							   =probability
               _UpperCAmelCase       :       List[Any]							   =k_state

            # Update probabilities and pointers dicts
         _UpperCAmelCase       :       str							   =(
             probabilities[(arg_max, prior_observation)]
             * transition_probabilities[arg_max][state]
             * emission_probabilities[state][observation]
         )

         _UpperCAmelCase       :       List[Any]							   =arg_max

    # The final observation
   _UpperCAmelCase       :       int							   =observations_space[len(__lowerCamelCase							) - 1]

   # argmax for given final observation
   _UpperCAmelCase       :       Any							   =''
   _UpperCAmelCase       :       Union[str, Any]							   =-1
   for k_state in states_space:
      _UpperCAmelCase       :       Optional[int]							   =probabilities[(k_state, final_observation)]
      if probability > max_probability:
         _UpperCAmelCase       :       Union[str, Any]							   =probability
         _UpperCAmelCase       :       int							   =k_state
   _UpperCAmelCase       :       int							   =arg_max

   # Process pointers backwards
   _UpperCAmelCase       :       List[str]							   =last_state
   _UpperCAmelCase       :       Optional[int]							   =[]
   for o in range(len(__lowerCamelCase							) - 1	,   -1	,   -1							):
      result.append(__lowerCamelCase							)
      _UpperCAmelCase       :       Optional[Any]							   =pointers[previous, observations_space[o]]
   result.reverse()

   return result





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_not_empty(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   _validate_lists(__lowerCamelCase	,   __lowerCamelCase							)
   _validate_dicts(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   if not all(
       [
           observations_space,
           states_space,
           initial_probabilities,
           transition_probabilities,
           emission_probabilities,
       ]							):
      raise ValueError('There\'s an empty parameter'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any							):







   '''simple docstring'''




   _validate_list(__lowerCamelCase	,   'observations_space'							)
   _validate_list(__lowerCamelCase	,   'states_space'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       Any							   =f"{var_name} must be a list"
      raise ValueError(__lowerCamelCase							)
   else:
      for x in _object:
         if not isinstance(__lowerCamelCase	,   __lowerCamelCase							):
            _UpperCAmelCase       :       Optional[int]							   =f"{var_name} must be a list of strings"
            raise ValueError(__lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_dict(__lowerCamelCase	,   'initial_probabilities'	,   __lowerCamelCase							)
   _validate_nested_dict(__lowerCamelCase	,   'transition_probabilities'							)
   _validate_nested_dict(__lowerCamelCase	,   'emission_probabilities'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   _validate_dict(_object	,   __lowerCamelCase	,   __lowerCamelCase							)
   for x in _object.values():
      _validate_dict(__lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str	,   __lowerCamelCase	:							type	,   __lowerCamelCase	:							bool = False							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       List[str]							   =f"{var_name} must be a dict"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object							):
      _UpperCAmelCase       :       str							   =f"{var_name} all keys must be strings"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object.values()							):
      _UpperCAmelCase       :       int							   ='nested dictionary ' if nested else ''
      _UpperCAmelCase       :       Optional[int]							   =f"{var_name} {nested_text}all values must be {value_type.__name__}"
      raise ValueError(__lowerCamelCase							)


if __name__ == "__main__":
 from doctest import testmod

 testmod()

