For example in a  class
def __init__():
  multi_output = [nn.Linear(50, 2) for i in range(10)]

def forward():
   outputs = [head(x) for head in multi_output]

Theoutputs keep changing in values at each run if I feed just a simple input tensor of 0’s.
No dropouts, running on eval().
Why would the ouputs keep changing at each run when I’m using the same model’s weights (network.load_state_dict())?