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Weight initialization schemes for PyTorch nn.Modules

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nninit

Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin.

##Update

This repo has been merged into PyTorch's nn module, I recommend you use that version going forward.

###PyTorch Example

import nninit
from torch import nn
import torch.nn.init as init
import numpy as np

class Net(nn.Module):
  def __init__(self):
     super(Net, self).__init__()
     self.conv1 = nn.Conv2d(5, 10, (3, 3))
     init.xavier_uniform(self.conv1.weight, gain=np.sqrt(2))
     init.constant(self.conv1.bias, 0.1)

network = Net()

##Installation Clone the repo and run python setup install

##Usage

import nninit
from torch import nn
import numpy as np

class Net(nn.Module):
  def __init__(self):
     super(Net, self).__init__()
     self.conv1 = nn.Conv2d(5, 10, (3, 3))
     nninit.xavier_uniform(self.conv1.weight, gain=np.sqrt(2))
     nninit.constant(self.conv1.bias, 0.1)

network = Net()

##Supported Schemes

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Weight initialization schemes for PyTorch nn.Modules

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