method: setFragmentTexture:atIndex:

method: setFrontFacingWinding:

method: setRenderPipelineState:atIndex:

method: setTriangleFillMode:

Dynamically set the experiment name

Example: from nerfstudio.configs import base_config base_config.CFG.xxx() FIXME: this is useless if the origi

Write the image over webrtc.

To be implemented.

Reducing the config settings to speedup test

Dynamically set the experiment timestamp

Sets up the data manager for evaluation

Helper to set up the optimizers Args: config: The trainer configuration object. param_groups: A dictionary of parameter groups to

Sets up the data manager for training. Here you will define any subclass specific object attributes from the attribute

Setup a zmq socket and connect it to the given url. Args: url: point of connection

Returns the number of elements in the tensor dataclass batch dimension.

! @brief skip the UTF-8 byte order mark @return true iff there is no BOM or the correct BOM has been skipped */

Perform iterative sphere tracing. ref: kaolin-wisp Returns: intersection_points: (..., 3) intersectio

! @brief split the string input to reference tokens @note This function is only called by the json_pointer constructor. All excepti

Squared symmetric epipolar distance. This can be seen as a biased estimation of the reprojection error. Args: pts0 (torch.Tensor): [N,

Test accumulation rendering

Test broadcasting during init

Test that the camera class move to Tensordataclass works.

Test rgb output

Test depth rendering

Test dnerf distortion

Test that the equirectangular camera model works.

Test render output

Test gaussian blob calculation

Test that dataclass is properly initialized

Test iterating over tensor dataclass

Test mlp

Test NeRF encoder

Test nested TensorDataclasses

Test pdf sampler

Test that the pinhole camera model works.

Test RFF encoder

Test rgb output

Test RGB volumetric rendering

Test scaling and offset encoder

Test sh output

Test SH volumetric rendering

Test the tiny-cuda-nn field

Test TensorCP encoder

Test Spherical Harmonic encoder

Test tensor operations

Test Spherical Harmonic encoder

Test TensorVM encoder

test run train script works properly

Test uniform sampler

property: textureType

Timeout if ping fails to complete in timeout_in_secs seconds

@brief create a CBOR serialization of a given JSON value @sa https://json.nlohmann.me/api/basic_json/to_cbor/

Converts this kind to a temporal distortion

Run one iteration with a batch of inputs. Returns dictionary of model losses. Args: step: Current training step.

Main training function that sets up and runs the trainer per process Args: local_rank: current rank of process world_size: total