metabci.brainda.algorithms.deep_learning package

Submodules

• metabci.brainda.algorithms.deep_learning.base module
  • AvgPool2dWithConv
    • AvgPool2dWithConv.forward()
    • AvgPool2dWithConv.training
  • Ensure4d
    • Ensure4d.forward()
    • Ensure4d.training
  • Expression
    • Expression.forward()
    • Expression.training
  • MaxNormConstraintConv2d
    • MaxNormConstraintConv2d.bias
    • MaxNormConstraintConv2d.dilation
    • MaxNormConstraintConv2d.forward()
    • MaxNormConstraintConv2d.groups
    • MaxNormConstraintConv2d.in_channels
    • MaxNormConstraintConv2d.kernel_size
    • MaxNormConstraintConv2d.out_channels
    • MaxNormConstraintConv2d.output_padding
    • MaxNormConstraintConv2d.padding
    • MaxNormConstraintConv2d.padding_mode
    • MaxNormConstraintConv2d.stride
    • MaxNormConstraintConv2d.transposed
    • MaxNormConstraintConv2d.weight
  • MaxNormConstraintLinear
    • MaxNormConstraintLinear.forward()
    • MaxNormConstraintLinear.in_features
    • MaxNormConstraintLinear.out_features
    • MaxNormConstraintLinear.weight
  • NeuralNetClassifierNoLog
    • NeuralNetClassifierNoLog.fit()
    • NeuralNetClassifierNoLog.get_loss()
  • SkorchNet
  • adaptive_batch_norm()
  • compute_out_size()
  • compute_same_pad1d()
  • compute_same_pad2d()
  • identity()
  • np_to_th()
  • squeeze_final_output()
  • transpose_time_to_spat()
• metabci.brainda.algorithms.deep_learning.convca module
• metabci.brainda.algorithms.deep_learning.deepnet module
• metabci.brainda.algorithms.deep_learning.eegnet module
  • SeparableConv2d
    • SeparableConv2d.forward()
    • SeparableConv2d.training
• metabci.brainda.algorithms.deep_learning.guney_net module
• metabci.brainda.algorithms.deep_learning.shallownet module
  • SafeLog
    • SafeLog.forward()
    • SafeLog.training
  • Square
    • Square.forward()
    • Square.training

Module contents