diff --git a/nerfstudio/field_components/encodings.py b/nerfstudio/field_components/encodings.py
index 462080287a..ac7cf2aa17 100644
--- a/nerfstudio/field_components/encodings.py
+++ b/nerfstudio/field_components/encodings.py
@@ -141,9 +141,9 @@ def forward(
         Returns:
             Output values will be between -1 and 1
         """
-        in_tensor = 2 * torch.pi * in_tensor  # scale to [0, 2pi]
+        scaled_in_tensor = 2 * torch.pi * in_tensor  # scale to [0, 2pi]
         freqs = 2 ** torch.linspace(self.min_freq, self.max_freq, self.num_frequencies).to(in_tensor.device)
-        scaled_inputs = in_tensor[..., None] * freqs  # [..., "input_dim", "num_scales"]
+        scaled_inputs = scaled_in_tensor[..., None] * freqs  # [..., "input_dim", "num_scales"]
         scaled_inputs = scaled_inputs.view(*scaled_inputs.shape[:-2], -1)  # [..., "input_dim" * "num_scales"]
 
         if covs is None:
@@ -201,8 +201,8 @@ def forward(
         Returns:
             Output values will be between -1 and 1
         """
-        in_tensor = 2 * torch.pi * in_tensor  # scale to [0, 2pi]
-        scaled_inputs = in_tensor @ self.b_matrix  # [..., "num_frequencies"]
+        scaled_in_tensor = 2 * torch.pi * in_tensor  # scale to [0, 2pi]
+        scaled_inputs = scaled_in_tensor @ self.b_matrix  # [..., "num_frequencies"]
 
         if covs is None:
             encoded_inputs = torch.sin(torch.cat([scaled_inputs, scaled_inputs + torch.pi / 2.0], dim=-1))