Merge pull request #46 from HighDimensionalEconLab/modification_bias_jan

different bias initialization

econ_layers/layers.py

@@ -17,18 +17,18 @@ def __init__(
     def forward(self, input):
         return torch.cat([input.pow(m) for m in torch.arange(1, self.n_moments + 1)], 1)
 
-    
+
 # rescaling by a specific element of a given input
 class RescaleOutputsByInput(nn.Module):
     def __init__(self, rescale_index: int = 0, bias=False):
         super().__init__()
         self.rescale_index = rescale_index
         if bias:
-            self.bias =  torch.nn.Parameter(torch.Tensor(1)) # only a scalar here
-            torch.nn.init.zeros_(self.bias)     
+            self.bias = torch.nn.Parameter(torch.Tensor(1))  # only a scalar here
+            torch.nn.init.ones_(self.bias)
         else:
-            self.bias = 0.0 # register_parameter('bias', None) # necessary?
-        
+            self.bias = 0.0  # register_parameter('bias', None) # necessary?
+
     def forward(self, x, y):
         if x.dim() == 1:
             return x[self.rescale_index] * y + self.bias