Merge pull request #35 from ruiqixu37/main

improve reproducibility

neural_style_field.py

@@ -9,7 +9,9 @@
 class ProgressiveEncoding(nn.Module):
     def __init__(self, mapping_size, T, d=3, apply=True):
         super(ProgressiveEncoding, self).__init__()
-        self._t = 0
+        self._t = nn.Parameter(
+            torch.tensor(0, dtype=torch.float32, device=device), requires_grad=False
+        )
         self.n = mapping_size
         self.T = T
         self.d = d

utils.py

@@ -1,4 +1,5 @@
 import torch
+import torch.nn as nn
 import kaolin as kal
 import clip
 import numpy as np
@@ -394,7 +395,7 @@ def __init__(self, num_input_channels, mapping_size=256, scale=10, exclude=0):
         self.exclude = exclude
         B = torch.randn((num_input_channels, mapping_size)) * scale
         B_sort = sorted(B, key=lambda x: torch.norm(x, p=2))
-        self._B = torch.stack(B_sort)  # for sape
+        self._B = nn.Parameter(torch.stack(B_sort), requires_grad=False)  # for sape
 
     def forward(self, x):
         # assert x.dim() == 4, 'Expected 4D input (got {}D input)'.format(x.dim())