List of fastai defaults

Trying to list some of the defaults used in fastai. I thought it would a good idea to have them in one place to refer in case we cannot use fastai for some project and in general to know what are the state-of-the-art practices.

  • torch.backends.cudnn.benchmark = True
  • (1e-7, 1-1e-7) for clamping.
  • Normalization layers bias=1e-3 and weight=0 or 1 depending on where the norm layer occurs.
  • Linear + activation + BatchNorm + Dropout.
  • Sigmoid clamped to (1e-7, 1-1e-7).
  • Leaky ReLU negative_slope=0.3.
  • Initialization used for a given activation function
Activation func Initialization
ReLU, ReLU6, LeakyReLU, Swish, Mish kaiming_uniform
Sigmoid, Tanh xavier_uniform
  • Initialization for Linear layer (includes conv layer also).
    • bias = normal(mean=0, std=0.01)
    • weight: the above table is used for this.
  • Conv layer
    • kernel_size=3
    • padding = (kernel_size-1)//2, zero for transposed conv.
    • BatchNorm, ReLU used.
    • Output is Convolution + BatchNorm + ReLU
  • Embedding layer initialized as, std=1).fmod_(2)
  • For merging skip-connections addition is used.

great idea.
this is something absolutely needed for any kind of high-level libraries