'''simple docstring'''


import subprocess
from argparse import ArgumentParser
from typing import List, Union

from huggingface_hub.hf_api import HfFolder, create_repo, whoami
from requests.exceptions import HTTPError

from . import BaseTransformersCLICommand






class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  @staticmethod
  def _UpperCamelCase     ( snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:   List[Any]   =      parser.add_parser('login'      ,		help='Log in using the same credentials as on huggingface.co'						)
       login_parser.set_defaults(func=lambda snake_case_						: LoginCommand(_UpperCamelCase						)						)
       UpperCAmelCase_							:   Optional[Any]   =      parser.add_parser('whoami'      ,		help='Find out which huggingface.co account you are logged in as.'						)
       whoami_parser.set_defaults(func=lambda snake_case_						: WhoamiCommand(_UpperCamelCase						)						)
       UpperCAmelCase_							:   List[str]   =      parser.add_parser('logout'      ,		help='Log out'						)
       logout_parser.set_defaults(func=lambda snake_case_						: LogoutCommand(_UpperCamelCase						)						)

       # new system: git-based repo system
       UpperCAmelCase_							:   str   =      parser.add_parser(
           'repo'      ,		help='Deprecated: use `huggingface-cli` instead. Commands to interact with your huggingface.co repos.'      ,		)
       UpperCAmelCase_							:   Any   =      repo_parser.add_subparsers(
           help='Deprecated: use `huggingface-cli` instead. huggingface.co repos related commands'						)
       UpperCAmelCase_							:   List[Any]   =      repo_subparsers.add_parser(
           'create'      ,		help='Deprecated: use `huggingface-cli` instead. Create a new repo on huggingface.co'						)
       repo_create_parser.add_argument(
           'name'      ,		type=_UpperCamelCase      ,		help='Name for your model\'s repo. Will be namespaced under your username to build the model id.'      ,		)
       repo_create_parser.add_argument('--organization'      ,		type=_UpperCamelCase      ,		help='Optional: organization namespace.'						)
       repo_create_parser.add_argument('-y'      ,		'--yes'      ,		action='store_true'      ,		help='Optional: answer Yes to the prompt'						)
       repo_create_parser.set_defaults(func=lambda snake_case_						: RepoCreateCommand(_UpperCamelCase						)						)







class      __SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  lowerCamelCase_		:str						    =		"""\u001b[1m"""
  lowerCamelCase_		:Dict						    =		"""\u001b[31m"""
  lowerCamelCase_		:str						    =		"""\u001b[90m"""
  lowerCamelCase_		:List[str]						    =		"""\u001b[0m"""


  @classmethod
  def _UpperCamelCase     ( cls      ,		snake_case_						):




       '''simple docstring'''

       return F'''{cls._bold}{s}{cls._reset}'''


  @classmethod
  def _UpperCamelCase     ( cls      ,		snake_case_						):




       '''simple docstring'''

       return F'''{cls._bold}{cls._red}{s}{cls._reset}'''






  @classmethod
  def _UpperCamelCase     ( cls      ,		snake_case_						):




       '''simple docstring'''

       return F'''{cls._gray}{s}{cls._reset}'''







def 					_lowerCamelCase    (      lowerCamelCase_					:							List[List[Union[str, int]]]	,     lowerCamelCase_					:							List[str]   ):



     """simple docstring"""





     UpperCAmelCase_							:   Union[str, Any]   =      [max(len(str(UpperCAmelCase__   )   ) for x in col   ) for col in zip(*UpperCAmelCase__	,     UpperCAmelCase__   )]
     UpperCAmelCase_							:   int   =      ('{{:{}}} ' * len(UpperCAmelCase__   )).format(*UpperCAmelCase__   )
     UpperCAmelCase_							:   Any   =      []
     lines.append(row_format.format(*UpperCAmelCase__   )   )
     lines.append(row_format.format(*['-' * w for w in col_widths]   )   )
     for row in rows:
          lines.append(row_format.format(*UpperCAmelCase__   )   )
     return "\n".join(UpperCAmelCase__   )






class      __SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__( self      ,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:   Optional[Any]   =      args







class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  def _UpperCamelCase     ( self						):




       '''simple docstring'''

       print(
           ANSI.red(
               'ERROR! `huggingface-cli login` uses an outdated login mechanism '
               'that is not compatible with the Hugging Face Hub backend anymore. '
               'Please use `huggingface-cli login instead.'						)						)







class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  def _UpperCamelCase     ( self						):




       '''simple docstring'''

       print(
           ANSI.red(
               'WARNING! `transformers-cli whoami` is deprecated and will be removed in v5. Please use '
               '`huggingface-cli whoami` instead.'						)						)
       UpperCAmelCase_							:   Optional[Any]   =      HfFolder.get_token()
       if token is None:
            print('Not logged in'						)
            exit()
       try:
            UpperCAmelCase_   ,			UpperCAmelCase_							:   Union[str, Any]   =      whoami(_UpperCamelCase						)
            print(_UpperCamelCase						)
            if orgs:
                 print(ANSI.bold('orgs: '						)      ,		','.join(_UpperCamelCase						)						)
       except HTTPError as e:
            print(_UpperCamelCase						)
            print(ANSI.red(e.response.text						)						)
            exit(1						)







class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  def _UpperCamelCase     ( self						):




       '''simple docstring'''

       print(
           ANSI.red(
               'ERROR! `transformers-cli logout` uses an outdated logout mechanism '
               'that is not compatible with the Hugging Face Hub backend anymore. '
               'Please use `huggingface-cli logout instead.'						)						)







class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  def _UpperCamelCase     ( self						):




       '''simple docstring'''

       print(
           ANSI.red(
               'WARNING! Managing repositories through transformers-cli is deprecated. '
               'Please use `huggingface-cli` instead.'						)						)
       UpperCAmelCase_							:   Dict   =      HfFolder.get_token()
       if token is None:
            print('Not logged in'						)
            exit(1						)
       try:
            UpperCAmelCase_							:   Optional[int]   =      subprocess.check_output(['git', '--version']						).decode('utf-8'						)
            print(ANSI.gray(stdout.strip()						)						)
       except FileNotFoundError:
            print('Looks like you do not have git installed, please install.'						)

       try:
            UpperCAmelCase_							:   Optional[int]   =      subprocess.check_output(['git-lfs', '--version']						).decode('utf-8'						)
            print(ANSI.gray(stdout.strip()						)						)
       except FileNotFoundError:
            print(
                ANSI.red(
                    'Looks like you do not have git-lfs installed, please install.'
                    ' You can install from https://git-lfs.github.com/.'
                    ' Then run `git lfs install` (you only have to do this once).'						)						)
       print(''						)

       UpperCAmelCase_   ,			UpperCAmelCase_							:   Union[str, Any]   =      whoami(_UpperCamelCase						)
       UpperCAmelCase_							:   Tuple   =      self.args.organization if self.args.organization is not None else user
       UpperCAmelCase_							:   Any   =      F'''{namespace}/{self.args.name}'''
       print(F'''You are about to create {ANSI.bold(_UpperCamelCase						)}'''						)

       if not self.args.yes:
            UpperCAmelCase_							:   List[Any]   =      input('Proceed? [Y/n] '						).lower()
            if not (choice == "" or choice == "y" or choice == "yes"):
                 print('Abort'						)
                 exit()
       try:
            UpperCAmelCase_							:   int   =      create_repo(_UpperCamelCase      ,		name=self.args.name      ,		organization=self.args.organization						)
       except HTTPError as e:
            print(_UpperCamelCase						)
            print(ANSI.red(e.response.text						)						)
            exit(1						)
       print('\nYour repo now lives at:'						)
       print(F'''  {ANSI.bold(_UpperCamelCase						)}'''						)
       print('\nYou can clone it locally with the command below, and commit/push as usual.'						)
       print(F'''\n  git clone {url}'''						)
       print(''						)







import random


class   lowercase			:




							def __init__(  self      :    List[Any]		,							_UpperCamelCase      :    list[list[float]]		,							_UpperCamelCase      :    list[int]		,							_UpperCamelCase      :    float = 0.0_1		,							_UpperCamelCase      :    int = 1_000		,							_UpperCamelCase      :    float = -1		,							)    -> None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE				=				sample
												if len(self.sample					) == 0:
																	raise ValueError("Sample data can not be empty"					)
												SCREAMING_SNAKE_CASE				=				target
												if len(self.target					) == 0:
																	raise ValueError("Target data can not be empty"					)
												if len(self.sample					) != len(self.target					):
																	raise ValueError("Sample data and Target data do not have matching lengths"					)
												SCREAMING_SNAKE_CASE				=				learning_rate
												SCREAMING_SNAKE_CASE				=				epoch_number
												SCREAMING_SNAKE_CASE				=				bias
												SCREAMING_SNAKE_CASE				=				len(_UpperCamelCase					)
												SCREAMING_SNAKE_CASE				=				len(sample[0]					)  # number of columns in dataset
												SCREAMING_SNAKE_CASE				=				[]




							def 		__snake_case(  self      :    Any					)    -> None:



												'''simple docstring'''

												for sample in self.sample:
																	sample.insert(0		,							self.bias					)

												for _ in range(self.col_sample					):
																	self.weight.append(random.random()					)

												self.weight.insert(0		,							self.bias					)

												SCREAMING_SNAKE_CASE				=				0

												while True:
																	SCREAMING_SNAKE_CASE				=				False
																	for i in range(self.number_sample					):
																						SCREAMING_SNAKE_CASE				=				0
																						for j in range(self.col_sample + 1					):
																											SCREAMING_SNAKE_CASE				=				u + self.weight[j] * self.sample[i][j]
																						SCREAMING_SNAKE_CASE				=				self.sign(_UpperCamelCase					)
																						if y != self.target[i]:
																											for j in range(self.col_sample + 1					):
																																SCREAMING_SNAKE_CASE				=				(
																																    self.weight[j]
																																    + self.learning_rate
																																    * (self.target[i] - y)
																																    * self.sample[i][j]
																																)
																											SCREAMING_SNAKE_CASE				=				True
            # print('Epoch: \n',epoch_count)
																	SCREAMING_SNAKE_CASE				=				epoch_count + 1
																	# if you want control the epoch or just by error
																	if not has_misclassified:
																						print(("\nEpoch:\n", epoch_count)					)
																						print("------------------------\n"					)
																						# if epoch_count > self.epoch_number or not error:
																						break




							def 		__snake_case(  self      :    Union[str, Any]		,							_UpperCamelCase      :    list[float]					)    -> None:



												'''simple docstring'''

												if len(self.sample					) == 0:
																	raise ValueError("Sample data can not be empty"					)
												sample.insert(0		,							self.bias					)
												SCREAMING_SNAKE_CASE				=				0
												for i in range(self.col_sample + 1					):
																	SCREAMING_SNAKE_CASE				=				u + self.weight[i] * sample[i]

												SCREAMING_SNAKE_CASE				=				self.sign(_UpperCamelCase					)

												if y == -1:
																	print(("Sample: ", sample)					)
																	print("classification: P1"					)
												else:
																	print(("Sample: ", sample)					)
																	print("classification: P2"					)





							def 		__snake_case(  self      :    Dict		,							_UpperCamelCase      :    float					)    -> int:



												'''simple docstring'''

												return 1 if u >= 0 else -1



_lowerCamelCase    :      Union[str, Any]	 =						[
    [-0.6_508, 0.1_097, 4.0_009],
    [-1.4_492, 0.8_896, 4.4_005],
    [2.0_850, 0.6_876, 12.0_710],
    [0.2_626, 1.1_476, 7.7_985],
    [0.6_418, 1.0_234, 7.0_427],
    [0.2_569, 0.6_730, 8.3_265],
    [1.1_155, 0.6_043, 7.4_446],
    [0.0_914, 0.3_399, 7.0_677],
    [0.0_121, 0.5_256, 4.6_316],
    [-0.0_429, 0.4_660, 5.4_323],
    [0.4_340, 0.6_870, 8.2_287],
    [0.2_735, 1.0_287, 7.1_934],
    [0.4_839, 0.4_851, 7.4_850],
    [0.4_089, -0.1_267, 5.5_019],
    [1.4_391, 0.1_614, 8.5_843],
    [-0.9_115, -0.1_973, 2.1_962],
    [0.3_654, 1.0_475, 7.4_858],
    [0.2_144, 0.7_515, 7.1_699],
    [0.2_013, 1.0_014, 6.5_489],
    [0.6_483, 0.2_183, 5.8_991],
    [-0.1_147, 0.2_242, 7.2_435],
    [-0.7_970, 0.8_795, 3.8_762],
    [-1.0_625, 0.6_366, 2.4_707],
    [0.5_307, 0.1_285, 5.6_883],
    [-1.2_200, 0.7_777, 1.7_252],
    [0.3_957, 0.1_076, 5.6_623],
    [-0.1_013, 0.5_989, 7.1_812],
    [2.4_482, 0.9_455, 11.2_095],
    [2.0_149, 0.6_192, 10.9_263],
    [0.2_012, 0.2_611, 5.4_631],
]

_lowerCamelCase    :      Optional[Any]	 =						[
    -1,
    -1,
    -1,
    1,
    1,
    -1,
    1,
    -1,
    1,
    1,
    -1,
    1,
    -1,
    -1,
    -1,
    -1,
    1,
    1,
    1,
    1,
    -1,
    1,
    1,
    1,
    1,
    -1,
    -1,
    1,
    -1,
    1,
]


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							_lowerCamelCase    :      Tuple	 =						Perceptron(
							    sample=samples, target=target, learning_rate=0.01, epoch_number=10_00, bias=-1
							)
							network.training()
							print('''Finished training perceptron''')
							print('''Enter values to predict or q to exit''')
							while True:
														_lowerCamelCase    :      list	 =						[]
														for i in range(len(samples[0])):
																					_lowerCamelCase    :      Dict	 =						input('''value: ''').strip()
																					if user_input == "q":
																												break
																					_lowerCamelCase    :      Any	 =						float(user_input)
																					sample.insert(i, observation)
														network.sort(sample)




