Improve comment

ml-agents/mlagents/trainers/torch/layers.py

     :param output_size: The size of the output tensor
     :param kernel_init: The Initialization to use for the weights of the layer
     :param kernel_gain: The multiplier for the weights of the kernel. Note that in
-    TensorFlow, the gain is square-rooted, and in Torch, it is set to a default value of sqrt(2).
-    Therefore calling variance_scaling with scale 0.01 is equivalent to calling
-    KaimingHeNormal with kernel_gain of 0.1 * sqrt(2)
+    TensorFlow, the gain is square-rooted. Therefore calling  with scale 0.01 is equivalent to calling
+        KaimingHeNormal with kernel_gain of 0.1
     :param bias_init: The Initialization to use for the weights of the bias layer
     """
     layer = torch.nn.Linear(input_size, output_size)