Knowing commited on
Commit
f747230
·
verified ·
1 Parent(s): 6d1e2ba

Add files using upload-large-folder tool

Browse files
re10k/RE10K_2v_level4/main.log CHANGED
@@ -48,3 +48,264 @@ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered int
48
  [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
49
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
50
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
48
  [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
49
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
50
 
51
+ [2026-03-09 08:45:15,794][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
52
+ result[selector] = overlay
53
+
54
+ [2026-03-09 08:46:58,676][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
55
+ result[selector] = overlay
56
+
57
+ [2026-03-09 08:48:42,825][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
58
+ result[selector] = overlay
59
+
60
+ [2026-03-09 08:50:26,439][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
61
+ result[selector] = overlay
62
+
63
+ [2026-03-09 08:52:09,930][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
64
+ result[selector] = overlay
65
+
66
+ [2026-03-09 08:53:52,829][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
67
+ result[selector] = overlay
68
+
69
+ [2026-03-09 08:55:37,592][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
70
+ result[selector] = overlay
71
+
72
+ [2026-03-09 08:57:21,751][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
73
+ result[selector] = overlay
74
+
75
+ [2026-03-09 08:57:25,470][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
76
+ result[selector] = overlay
77
+
78
+ [2026-03-09 08:57:28,792][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
79
+ result[selector] = overlay
80
+
81
+ [2026-03-09 08:59:06,105][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
82
+ result[selector] = overlay
83
+
84
+ [2026-03-09 09:00:50,011][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
85
+ result[selector] = overlay
86
+
87
+ [2026-03-09 09:02:33,981][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
88
+ result[selector] = overlay
89
+
90
+ [2026-03-09 09:04:17,752][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
91
+ result[selector] = overlay
92
+
93
+ [2026-03-09 09:06:00,800][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
94
+ result[selector] = overlay
95
+
96
+ [2026-03-09 09:07:45,093][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
97
+ result[selector] = overlay
98
+
99
+ [2026-03-09 09:09:29,294][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
100
+ result[selector] = overlay
101
+
102
+ [2026-03-09 09:11:12,140][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
103
+ result[selector] = overlay
104
+
105
+ [2026-03-09 09:11:15,805][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
106
+ result[selector] = overlay
107
+
108
+ [2026-03-09 09:11:19,860][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
109
+ result[selector] = overlay
110
+
111
+ [2026-03-09 09:12:58,755][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
112
+ result[selector] = overlay
113
+
114
+ [2026-03-09 09:14:44,047][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
115
+ result[selector] = overlay
116
+
117
+ [2026-03-09 09:16:28,186][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
118
+ result[selector] = overlay
119
+
120
+ [2026-03-09 09:18:10,273][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
121
+ result[selector] = overlay
122
+
123
+ [2026-03-09 09:19:53,888][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
124
+ result[selector] = overlay
125
+
126
+ [2026-03-09 09:21:38,006][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
127
+ result[selector] = overlay
128
+
129
+ [2026-03-09 09:23:20,934][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
130
+ result[selector] = overlay
131
+
132
+ [2026-03-09 09:25:05,156][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
133
+ result[selector] = overlay
134
+
135
+ [2026-03-09 09:25:09,026][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
136
+ result[selector] = overlay
137
+
138
+ [2026-03-09 09:25:11,922][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
139
+ result[selector] = overlay
140
+
141
+ [2026-03-09 09:26:51,365][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
142
+ result[selector] = overlay
143
+
144
+ [2026-03-09 09:28:34,910][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
145
+ result[selector] = overlay
146
+
147
+ [2026-03-09 09:30:18,410][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
148
+ result[selector] = overlay
149
+
150
+ [2026-03-09 09:32:01,125][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
151
+ result[selector] = overlay
152
+
153
+ [2026-03-09 09:33:43,888][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
154
+ result[selector] = overlay
155
+
156
+ [2026-03-09 09:35:27,895][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
157
+ result[selector] = overlay
158
+
159
+ [2026-03-09 09:37:12,747][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
160
+ result[selector] = overlay
161
+
162
+ [2026-03-09 09:38:55,875][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
163
+ result[selector] = overlay
164
+
165
+ [2026-03-09 09:38:58,980][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
166
+ result[selector] = overlay
167
+
168
+ [2026-03-09 09:39:01,907][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
169
+ result[selector] = overlay
170
+
171
+ [2026-03-09 09:40:40,835][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
172
+ result[selector] = overlay
173
+
174
+ [2026-03-09 09:42:26,309][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
175
+ result[selector] = overlay
176
+
177
+ [2026-03-09 09:44:10,423][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
178
+ result[selector] = overlay
179
+
180
+ [2026-03-09 09:45:56,204][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
181
+ result[selector] = overlay
182
+
183
+ [2026-03-09 09:47:40,510][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
184
+ result[selector] = overlay
185
+
186
+ [2026-03-09 09:49:23,784][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
187
+ result[selector] = overlay
188
+
189
+ [2026-03-09 09:51:07,165][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
190
+ result[selector] = overlay
191
+
192
+ [2026-03-09 09:52:50,404][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
193
+ result[selector] = overlay
194
+
195
+ [2026-03-09 09:52:55,207][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
196
+ result[selector] = overlay
197
+
198
+ [2026-03-09 09:52:58,932][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
199
+ result[selector] = overlay
200
+
201
+ [2026-03-09 09:54:37,795][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
202
+ result[selector] = overlay
203
+
204
+ [2026-03-09 09:56:21,584][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
205
+ result[selector] = overlay
206
+
207
+ [2026-03-09 09:58:04,040][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
208
+ result[selector] = overlay
209
+
210
+ [2026-03-09 09:59:46,891][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
211
+ result[selector] = overlay
212
+
213
+ [2026-03-09 10:01:29,650][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
214
+ result[selector] = overlay
215
+
216
+ [2026-03-09 10:03:13,891][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
217
+ result[selector] = overlay
218
+
219
+ [2026-03-09 10:04:56,528][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
220
+ result[selector] = overlay
221
+
222
+ [2026-03-09 10:06:39,732][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
223
+ result[selector] = overlay
224
+
225
+ [2026-03-09 10:06:43,025][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
226
+ result[selector] = overlay
227
+
228
+ [2026-03-09 10:06:45,991][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
229
+ result[selector] = overlay
230
+
231
+ [2026-03-09 10:08:25,131][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
232
+ result[selector] = overlay
233
+
234
+ [2026-03-09 10:10:09,781][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
235
+ result[selector] = overlay
236
+
237
+ [2026-03-09 10:11:54,333][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
238
+ result[selector] = overlay
239
+
240
+ [2026-03-09 10:13:38,555][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
241
+ result[selector] = overlay
242
+
243
+ [2026-03-09 10:15:22,852][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
244
+ result[selector] = overlay
245
+
246
+ [2026-03-09 10:17:08,011][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
247
+ result[selector] = overlay
248
+
249
+ [2026-03-09 10:18:51,023][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
250
+ result[selector] = overlay
251
+
252
+ [2026-03-09 10:20:34,063][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
253
+ result[selector] = overlay
254
+
255
+ [2026-03-09 10:20:37,805][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
256
+ result[selector] = overlay
257
+
258
+ [2026-03-09 10:20:41,539][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
259
+ result[selector] = overlay
260
+
261
+ [2026-03-09 10:22:19,803][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
262
+ result[selector] = overlay
263
+
264
+ [2026-03-09 10:24:04,531][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
265
+ result[selector] = overlay
266
+
267
+ [2026-03-09 10:25:48,084][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
268
+ result[selector] = overlay
269
+
270
+ [2026-03-09 10:27:31,009][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
271
+ result[selector] = overlay
272
+
273
+ [2026-03-09 10:29:13,528][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
274
+ result[selector] = overlay
275
+
276
+ [2026-03-09 10:30:57,188][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
277
+ result[selector] = overlay
278
+
279
+ [2026-03-09 10:32:40,109][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
280
+ result[selector] = overlay
281
+
282
+ [2026-03-09 10:34:24,168][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
283
+ result[selector] = overlay
284
+
285
+ [2026-03-09 10:34:28,554][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
286
+ result[selector] = overlay
287
+
288
+ [2026-03-09 10:34:32,248][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
289
+ result[selector] = overlay
290
+
291
+ [2026-03-09 10:36:11,850][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
292
+ result[selector] = overlay
293
+
294
+ [2026-03-09 10:37:55,304][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
295
+ result[selector] = overlay
296
+
297
+ [2026-03-09 10:39:38,970][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
298
+ result[selector] = overlay
299
+
300
+ [2026-03-09 10:41:23,274][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
301
+ result[selector] = overlay
302
+
303
+ [2026-03-09 10:43:05,908][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
304
+ result[selector] = overlay
305
+
306
+ [2026-03-09 10:44:49,730][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
307
+ result[selector] = overlay
308
+
309
+ [2026-03-09 10:46:33,292][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
310
+ result[selector] = overlay
311
+
re10k/RE10K_2v_level4/train_ddp_process_1.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:26,578][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:44,736][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:44,737][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:34,384][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,701][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,800][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,826][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,154][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,788][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:13,627][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,002][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,920][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,446][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,604][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,398][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,989][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,842][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,538][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,735][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_2.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:27,114][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:50,293][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:50,294][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:34,995][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,698][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,813][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,395][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,788][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:13,926][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,588][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,920][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,499][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,907][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,442][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,370][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,989][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,688][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,538][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,533][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_3.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:26,621][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:46,371][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:46,371][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:35,390][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,698][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,156][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,786][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:13,721][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,859][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,111][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,920][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,441][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,504][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,849][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,990][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,838][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,538][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,610][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_4.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:26,590][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:45,931][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:45,933][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:34,672][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,701][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,804][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,339][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,788][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:14,276][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,859][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,276][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,921][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,392][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,448][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,325][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,989][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,726][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,537][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,785][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_5.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:26,830][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:47,155][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:47,156][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:35,640][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,699][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,859][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,273][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,786][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:13,675][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,510][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,920][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,296][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,458][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,381][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,989][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,699][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,537][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,641][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_6.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:27,547][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:54,689][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:54,689][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:33,923][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,703][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,832][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,825][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,107][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,786][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:14,269][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,159][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,920][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,487][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,361][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,394][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,989][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,581][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,537][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,534][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,246][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+
re10k/RE10K_2v_level4/train_ddp_process_7.log ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2026-03-09 08:42:33,139][dinov2][INFO] - using MLP layer as FFN
2
+ [2026-03-09 08:42:54,657][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
3
+ warnings.warn(
4
+
5
+ [2026-03-09 08:42:54,657][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
6
+ warnings.warn(msg)
7
+
8
+ [2026-03-09 08:43:13,706][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
9
+ warnings.warn( # warn only once
10
+
11
+ [2026-03-09 08:43:33,504][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
12
+ result[selector] = overlay
13
+
14
+ [2026-03-09 08:43:37,705][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
15
+ grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
16
+ bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
17
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
18
+
19
+ [2026-03-09 08:43:37,813][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
20
+ result[selector] = overlay
21
+
22
+ [2026-03-09 08:44:34,797][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
23
+ warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
24
+
25
+ [2026-03-09 08:57:23,350][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
26
+ result[selector] = overlay
27
+
28
+ [2026-03-09 08:57:28,787][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
29
+ result[selector] = overlay
30
+
31
+ [2026-03-09 09:11:13,783][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
32
+ result[selector] = overlay
33
+
34
+ [2026-03-09 09:11:19,858][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
35
+ result[selector] = overlay
36
+
37
+ [2026-03-09 09:25:06,173][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
38
+ result[selector] = overlay
39
+
40
+ [2026-03-09 09:25:11,921][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
41
+ result[selector] = overlay
42
+
43
+ [2026-03-09 09:38:57,328][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
44
+ result[selector] = overlay
45
+
46
+ [2026-03-09 09:39:01,906][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
47
+ result[selector] = overlay
48
+
49
+ [2026-03-09 09:52:51,511][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
50
+ result[selector] = overlay
51
+
52
+ [2026-03-09 09:52:58,929][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
53
+ result[selector] = overlay
54
+
55
+ [2026-03-09 10:06:41,415][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
56
+ result[selector] = overlay
57
+
58
+ [2026-03-09 10:06:45,991][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
59
+ result[selector] = overlay
60
+
61
+ [2026-03-09 10:20:35,644][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
62
+ result[selector] = overlay
63
+
64
+ [2026-03-09 10:20:41,538][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
65
+ result[selector] = overlay
66
+
67
+ [2026-03-09 10:34:25,573][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
68
+ result[selector] = overlay
69
+
70
+ [2026-03-09 10:34:32,248][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
71
+ result[selector] = overlay
72
+