llrt

/

G-NeRF

like 0

• "torch._utils._rebuild_parameter",
• "numpy.dtype",
• "dnnlib.util.EasyDict",
• "training.volumetric_rendering.ray_sampler.RaySampler",
• "torch._utils._rebuild_tensor_v2",
• "torch_utils.persistence._reconstruct_persistent_obj",
• "training.volumetric_rendering.renderer.ImportanceRenderer",
• "torch.storage._load_from_bytes",
• "training.volumetric_rendering.ray_marcher.MipRayMarcher2",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.activation.Softplus",
• "collections.OrderedDict",
• "training.triplane.OSGDecoder",
• "numpy.core.multiarray.scalar"

How to fix it?

• "torch.storage._load_from_bytes",
• "torchvision.models.resnet.Bottleneck",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.Sequential",
• "torch_utils.persistence._reconstruct_persistent_obj",
• "torch.nn.modules.conv.Conv2d",
• "torchvision.models.resnet.ResNet",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.activation.ReLU",
• "collections.OrderedDict",
• "torch.nn.modules.batchnorm.SyncBatchNorm"

How to fix it?

• "torch.storage._load_from_bytes",
• "training.volumetric_rendering.renderer.ImportanceRenderer",
• "torch._utils._rebuild_parameter",
• "numpy.dtype",
• "training.triplane.OSGDecoder",
• "dnnlib.util.EasyDict",
• "torch.nn.modules.container.Sequential",
• "torch_utils.persistence._reconstruct_persistent_obj",
• "torch.nn.modules.activation.Softplus",
• "training.volumetric_rendering.ray_sampler.RaySampler",
• "torch._utils._rebuild_tensor_v2",
• "numpy.core.multiarray.scalar",
• "collections.OrderedDict",
• "training.volumetric_rendering.ray_marcher.MipRayMarcher2"

How to fix it?