code: 
  
  
  """simple docstring"""
  import numpy as np
  from matplotlib import pyplot as plt
  
  def 							_snake_case			(      __snake_case       :			List[str]      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     return 1 / (1 + np.exp(-1 * x      ))
  
  
  
  
  class   lowercase__							:
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE=None			,      SCREAMING_SNAKE_CASE=None			,      SCREAMING_SNAKE_CASE=False)     ->     str:
        _lowerCamelCase  :				str      =		units
        _lowerCamelCase  :				str      =		None
        _lowerCamelCase  :				Dict      =		None
        _lowerCamelCase  :				List[Any]      =		activation
        if learning_rate is None:
           _lowerCamelCase  :				Tuple      =		0.3
        _lowerCamelCase  :				int      =		learning_rate
        _lowerCamelCase  :				Any      =		is_input_layer
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     Dict:
        _lowerCamelCase  :				List[Any]      =		np.asmatrix(np.random.normal(0			,      0.5			,      (self.units, back_units)))
        _lowerCamelCase  :				Tuple      =		np.asmatrix(np.random.normal(0			,      0.5			,      self.units)).T
        if self.activation is None:
           _lowerCamelCase  :				Tuple      =		sigmoid
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Optional[Any]:
        # activation function may be sigmoid or linear
        if self.activation == sigmoid:
           _lowerCamelCase  :				Tuple      =		np.dot(self.output			,      (1 - self.output).T)
           _lowerCamelCase  :				Dict      =		np.diag(np.diag(SCREAMING_SNAKE_CASE))
        else:
           _lowerCamelCase  :				str      =		1
        return gradient_activation
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     Any:
        _lowerCamelCase  :				List[Any]      =		xdata
        if self.is_input_layer:
           # input layer
           _lowerCamelCase  :				Tuple      =		xdata
           _lowerCamelCase  :				int      =		xdata
           return xdata
        else:
           _lowerCamelCase  :				List[str]      =		np.dot(self.weight			,      self.xdata) - self.bias
           _lowerCamelCase  :				Optional[Any]      =		self.activation(self.wx_plus_b)
           return self.output
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     List[str]:
        _lowerCamelCase  :				Union[str, Any]      =		self.cal_gradient()  # i * i 维
        _lowerCamelCase  :				Union[str, Any]      =		np.asmatrix(np.dot(gradient.T			,      SCREAMING_SNAKE_CASE))
  
        _lowerCamelCase  :				Optional[int]      =		np.asmatrix(self.xdata)
        _lowerCamelCase  :				str      =		-1
        _lowerCamelCase  :				Optional[int]      =		self.weight
  
        _lowerCamelCase  :				Optional[Any]      =		np.dot(gradient.T			,      self._gradient_weight.T)
        _lowerCamelCase  :				List[Any]      =		gradient * self._gradient_bias
        _lowerCamelCase  :				List[str]      =		np.dot(SCREAMING_SNAKE_CASE			,      self._gradient_x).T
        # upgrade: the Negative gradient direction
        _lowerCamelCase  :				Union[str, Any]      =		self.weight - self.learn_rate * self.gradient_weight
        _lowerCamelCase  :				str      =		self.bias - self.learn_rate * self.gradient_bias.T
        # updates the weights and bias according to learning rate (0.3 if undefined)
        return self.gradient
  
  
  
  
  
  
  
  class   lowercase__							:
  
  
  
  
  
     def __init__(       self)     ->     Any:
        _lowerCamelCase  :				Union[str, Any]      =		[]
        _lowerCamelCase  :				int      =		[]
        _lowerCamelCase  :				Union[str, Any]      =		plt.figure()
        _lowerCamelCase  :				Optional[int]      =		self.fig_loss.add_subplot(1			,      1			,      1)
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     int:
        self.layers.append(SCREAMING_SNAKE_CASE)
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Union[str, Any]:
        for i, layer in enumerate(self.layers[:]):
           if i < 1:
              _lowerCamelCase  :				Optional[int]      =		True
           else:
              layer.initializer(self.layers[i - 1].units)
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Optional[Any]:
        for i, layer in enumerate(self.layers[:]):
           print(F'------- layer {i} -------')
           print("""weight.shape """			,      np.shape(layer.weight))
           print("""bias.shape """			,      np.shape(layer.bias))
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     str:
        _lowerCamelCase  :				int      =		train_round
        _lowerCamelCase  :				List[str]      =		accuracy
  
        self.ax_loss.hlines(self.accuracy			,      0			,      self.train_round * 1.1)
  
        _lowerCamelCase  :				Tuple      =		np.shape(SCREAMING_SNAKE_CASE)
        for _ in range(SCREAMING_SNAKE_CASE):
           _lowerCamelCase  :				List[str]      =		0
           for row in range(x_shape[0]):
              _lowerCamelCase  :				List[Any]      =		np.asmatrix(xdata[row, :]).T
              _lowerCamelCase  :				int      =		np.asmatrix(ydata[row, :]).T
  
              # forward propagation
              for layer in self.layers:
                 _lowerCamelCase  :				Optional[Any]      =		layer.forward_propagation(_xdata)
  
              _lowerCamelCase  :				List[Any]      =		self.cal_loss(_ydata			,      _xdata)
              _lowerCamelCase  :				str      =		all_loss + loss
  
              # back propagation: the input_layer does not upgrade
              for layer in self.layers[:0:-1]:
                 _lowerCamelCase  :				str      =		layer.back_propagation(SCREAMING_SNAKE_CASE)
  
           _lowerCamelCase  :				Union[str, Any]      =		all_loss / x_shape[0]
           self.train_mse.append(SCREAMING_SNAKE_CASE)
  
           self.plot_loss()
  
           if mse < self.accuracy:
              print("""----达到精度----""")
              return mse
        return None
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     int:
        _lowerCamelCase  :				List[str]      =		np.sum(np.power((ydata - ydata_)			,      2))
        _lowerCamelCase  :				Optional[int]      =		2 * (ydata_ - ydata)
        # vector (shape is the same as _ydata.shape)
        return self.loss, self.loss_gradient
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Tuple:
        if self.ax_loss.lines:
           self.ax_loss.lines.remove(self.ax_loss.lines[0])
        self.ax_loss.plot(self.train_mse			,      """r-""")
        plt.ion()
        plt.xlabel("""step""")
        plt.ylabel("""loss""")
        plt.show()
        plt.pause(0.1)
  
  
  
  
  
  
  
  def 							_snake_case			(      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				List[str]      =		np.random.randn(10	,   10      )
     _lowerCamelCase  :				List[Any]      =		np.asarray(
         [
             [0.8, 0.4],
             [0.4, 0.3],
             [0.34, 0.45],
             [0.67, 0.32],
             [0.88, 0.67],
             [0.78, 0.77],
             [0.55, 0.66],
             [0.55, 0.43],
             [0.54, 0.1],
             [0.1, 0.5],
         ]      )
     _lowerCamelCase  :				Dict      =		BPNN()
     for i in (10, 20, 30, 2):
        model.add_layer(DenseLayer(__snake_case      )      )
     model.build()
     model.summary()
     model.train(xdata=__snake_case	,   ydata=__snake_case	,   train_round=100	,   accuracy=0.01      )
  
  
  if __name__ == "__main__":
   example()
  
  
  
  
  
  
  
style_context: 
  
  
  """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   lowercase__							(				A_							):
  
  
  
  
  
     @staticmethod
     def 		UpperCamelCase_     (       SCREAMING_SNAKE_CASE)     ->     Dict:
        _lowerCamelCase  :				Optional[Any]      =		parser.add_parser("""login"""			,      help="""Log in using the same credentials as on huggingface.co""")
        login_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE: LoginCommand(SCREAMING_SNAKE_CASE))
        _lowerCamelCase  :				Any      =		parser.add_parser("""whoami"""			,      help="""Find out which huggingface.co account you are logged in as.""")
        whoami_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE: WhoamiCommand(SCREAMING_SNAKE_CASE))
        _lowerCamelCase  :				Optional[int]      =		parser.add_parser("""logout"""			,      help="""Log out""")
        logout_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE: LogoutCommand(SCREAMING_SNAKE_CASE))
  
        # new system: git-based repo system
        _lowerCamelCase  :				Optional[int]      =		parser.add_parser(
            """repo"""			,      help="""Deprecated: use `huggingface-cli` instead. Commands to interact with your huggingface.co repos."""			,      )
        _lowerCamelCase  :				Optional[Any]      =		repo_parser.add_subparsers(
            help="""Deprecated: use `huggingface-cli` instead. huggingface.co repos related commands""")
        _lowerCamelCase  :				Dict      =		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=SCREAMING_SNAKE_CASE			,      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=SCREAMING_SNAKE_CASE			,      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 SCREAMING_SNAKE_CASE: RepoCreateCommand(SCREAMING_SNAKE_CASE))
  
  
  
  
  
  
  
  class   lowercase__							:
     __UpperCAmelCase       					=				'''\u001b[1m'''
     __UpperCAmelCase       					=				'''\u001b[31m'''
     __UpperCAmelCase       					=				'''\u001b[90m'''
     __UpperCAmelCase       					=				'''\u001b[0m'''
  
  
  
  
  
     @classmethod
     def 		UpperCamelCase_     (       cls			,      SCREAMING_SNAKE_CASE)     ->     Dict:
        return F'{cls._bold}{s}{cls._reset}'
  
  
  
  
  
     @classmethod
     def 		UpperCamelCase_     (       cls			,      SCREAMING_SNAKE_CASE)     ->     Union[str, Any]:
        return F'{cls._bold}{cls._red}{s}{cls._reset}'
  
  
  
  
  
     @classmethod
     def 		UpperCamelCase_     (       cls			,      SCREAMING_SNAKE_CASE)     ->     Tuple:
        return F'{cls._gray}{s}{cls._reset}'
  
  
  
  
  
  
  
  def 							_snake_case			(      __snake_case       :			List[List[Union[str, int]]]	,   __snake_case       :			List[str]      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				str      =		[max(len(str(__snake_case      )      ) for x in col      ) for col in zip(*__snake_case	,   __snake_case      )]
     _lowerCamelCase  :				Any      =		("""{{:{}}} """ * len(__snake_case      )).format(*__snake_case      )
     _lowerCamelCase  :				Optional[Any]      =		[]
     lines.append(row_format.format(*__snake_case      )      )
     lines.append(row_format.format(*["""-""" * w for w in col_widths]      )      )
     for row in rows:
        lines.append(row_format.format(*__snake_case      )      )
     return "\n".join(__snake_case      )
  
  
  
  
  class   lowercase__							:
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE)     ->     List[str]:
        _lowerCamelCase  :				Any      =		args
  
  
  
  
  
  
  
  class   lowercase__							(				A_							):
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     int:
        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   lowercase__							(				A_							):
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Tuple:
        print(
            ANSI.red(
                """WARNING! `transformers-cli whoami` is deprecated and will be removed in v5. Please use """
                """`huggingface-cli whoami` instead."""))
        _lowerCamelCase  :				Tuple      =		HfFolder.get_token()
        if token is None:
           print("""Not logged in""")
           exit()
        try:
           _lowerCamelCase      ,						_lowerCamelCase  :				int      =		whoami(SCREAMING_SNAKE_CASE)
           print(SCREAMING_SNAKE_CASE)
           if orgs:
              print(ANSI.bold("""orgs: """)			,      """,""".join(SCREAMING_SNAKE_CASE))
        except HTTPError as e:
           print(SCREAMING_SNAKE_CASE)
           print(ANSI.red(e.response.text))
           exit(1)
  
  
  
  
  
  
  
  class   lowercase__							(				A_							):
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Union[str, Any]:
        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   lowercase__							(				A_							):
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     List[Any]:
        print(
            ANSI.red(
                """WARNING! Managing repositories through transformers-cli is deprecated. """
                """Please use `huggingface-cli` instead."""))
        _lowerCamelCase  :				Union[str, Any]      =		HfFolder.get_token()
        if token is None:
           print("""Not logged in""")
           exit(1)
        try:
           _lowerCamelCase  :				Union[str, Any]      =		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:
           _lowerCamelCase  :				List[str]      =		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("""""")
  
        _lowerCamelCase      ,						_lowerCamelCase  :				str      =		whoami(SCREAMING_SNAKE_CASE)
        _lowerCamelCase  :				str      =		self.args.organization if self.args.organization is not None else user
        _lowerCamelCase  :				Union[str, Any]      =		F'{namespace}/{self.args.name}'
        print(F'You are about to create {ANSI.bold(SCREAMING_SNAKE_CASE)}')
  
        if not self.args.yes:
           _lowerCamelCase  :				Tuple      =		input("""Proceed? [Y/n] """).lower()
           if not (choice == "" or choice == "y" or choice == "yes"):
              print("""Abort""")
              exit()
        try:
           _lowerCamelCase  :				int      =		create_repo(SCREAMING_SNAKE_CASE			,      name=self.args.name			,      organization=self.args.organization)
        except HTTPError as e:
           print(SCREAMING_SNAKE_CASE)
           print(ANSI.red(e.response.text))
           exit(1)
        print("""\nYour repo now lives at:""")
        print(F'  {ANSI.bold(SCREAMING_SNAKE_CASE)}')
        print("""\nYou can clone it locally with the command below, and commit/push as usual.""")
        print(F'\n  git clone {url}')
        print("""""")
  
  