Comments (2)
Hi Stavros, that's strange -- it should work. I quickly tried your config in our radiance caching code and it works fine on my machine.
For reference, here's the config we used in the paper and which I also confirmed working on latest tiny-cuda-nn:
{
"loss": {
"otype": "RelativeL2Luminance"
},
"optimizer": {
"otype": "Ema",
"decay": 0.99,
"sensitivity": 0.1,
"nested": {
"otype": "ExponentialDecay",
"decay_start": 4000,
"decay_interval": 4000,
"decay_base": 0.33,
"nested": {
"otype": "Adam",
"learning_rate": 1e-2,
"beta1": 0.9,
"beta2": 0.99,
"epsilon": 1e-15,
"l2_reg": 1e-6
}
}
},
"encoding": {
"otype": "Composite",
"nested": [
{
"n_dims_to_encode": 3, // Position
"otype": "HashGrid",
"per_level_scale": 2.0,
"log2_hashmap_size": 15,
"base_resolution": 16,
"n_levels": 16
},
{
"n_dims_to_encode": 5, // Interesting conditionals
"otype": "OneBlob",
"n_bins": 4
},
{
"n_dims_to_encode": 6, // Linear conditionals that should be identity encoded
"otype": "Identity"
}
]
},
"network": {
"otype": "FullyFusedMLP",
"activation": "ReLU",
"output_activation": "None",
"n_neurons": 64,
"n_hidden_layers": 2
}
}
To troubleshoot further:
- could you let me know which call is throwing the exception?
- are you using the config to instantiate a
NetworkWithInputEncoding
and are there any implementation details you can divulge about how the network/encoding is called? - there might be something wrong with the input / output buffer sizes and the illegal memory access -- being undefined behavior -- only surfaces with some code paths.
Cheers!
from tiny-cuda-nn.
Closing on the assumption that the problem is solved by now. Please feel free to re-open and provide extra details if not.
from tiny-cuda-nn.
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