old_contents: from . import dataset
  from . import expr
  from . import misc
  from . import model
  from .autoencoder.autoencoder import Autoencoder, DenoisingAutoencoder
  from .autoencoder.stacked_autoencoder import StackedAutoencoder
  from .base import bool_, int_, float_
  from .feedforward.activation_layers import (
      Activation, LeakyReLU, ParametricReLU, ReLU, Sigmoid, Softmax, Softplus,
      Tanh
  )
  from .feedforward.neural_network import NeuralNetwork
  from .feedforward.layers import Affine
  from .feedforward.dropout_layers import Dropout
  from .feedforward.convnet_layers import (
      Convolution, Flatten, Pool, LocalContrastNormalization,
      LocalResponseNormalization
  )
  from .filler import (
      AutoFiller, CopyFiller, ConstantFiller, NormalFiller, UniformFiller
  )
  from .input import Input, SupervisedInput
  from .loss import SoftmaxCrossEntropy, BinaryCrossEntropy, MeanSquaredError
  from .parameter import Parameter
  from .preprocess.scalers import StandardScaler, UniformScaler
  from .siamese.input import SiameseInput, SupervisedSiameseInput
  from .siamese.loss import ContrastiveLoss
  from .siamese.siamese_network import SiameseNetwork
  from .train.annealers import ZeroAnnealer, DecayAnnealer, GammaAnnealer
  from .train.learn_rules import Adam, Momentum, RMSProp
  from .train.gradient_descent import GradientDescent
  
  __version__ = '0.1.dev'
  
new_contents: __version__ = '0.1.dev'
  
  import os
  import logging
  
  debug_mode = os.getenv('DEEPPY_DEBUG', '')
  debug_mode = None if debug_mode == '' else debug_mode.lower()
  
  from . import dataset
  from . import expr
  from . import misc
  from . import model
  from .autoencoder.autoencoder import Autoencoder, DenoisingAutoencoder
  from .autoencoder.stacked_autoencoder import StackedAutoencoder
  from .base import bool_, int_, float_
  from .feedforward.activation_layers import (
      Activation, LeakyReLU, ParametricReLU, ReLU, Sigmoid, Softmax, Softplus,
      Tanh
  )
  from .feedforward.neural_network import NeuralNetwork
  from .feedforward.layers import Affine
  from .feedforward.dropout_layers import Dropout
  from .feedforward.convnet_layers import (
      Convolution, Flatten, Pool, LocalContrastNormalization,
      LocalResponseNormalization
  )
  from .filler import (
      AutoFiller, CopyFiller, ConstantFiller, NormalFiller, UniformFiller
  )
  from .input import Input, SupervisedInput
  from .loss import SoftmaxCrossEntropy, BinaryCrossEntropy, MeanSquaredError
  from .parameter import Parameter
  from .preprocess.scalers import StandardScaler, UniformScaler
  from .siamese.input import SiameseInput, SupervisedSiameseInput
  from .siamese.loss import ContrastiveLoss
  from .siamese.siamese_network import SiameseNetwork
  from .train.annealers import ZeroAnnealer, DecayAnnealer, GammaAnnealer
  from .train.learn_rules import Adam, Momentum, RMSProp
  from .train.gradient_descent import GradientDescent
  
  
  log = logging.getLogger(__name__)
  if debug_mode is not None:
      log.info('DeepPy in debug mode: %s' % debug_mode)
  
subject: add debug_mode