- nvidia.dali.plugin.pytorch.fn.torch_python_function(*inputs, **kwargs)¶
Executes a function that is operating on Torch tensors.
This class is analogous to
nvidia.dali.fn.python_function()but the tensor data is handled as PyTorch tensors.
This operator allows sequence inputs and supports volumetric data.
This operator will not be optimized out of the graph.
- Supported backends
input[0..255] (TensorList, optional) – This function accepts up to 256 optional positional inputs
- Keyword Arguments:
function (object) – Function object.
batch_processing (bool, optional, default = False) – Determines whether the function gets an entire batch as an input.
bytes_per_sample_hint (int or list of int, optional, default = ) –
Output size hint, in bytes per sample.
If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
num_outputs (int, optional, default = 1) – Number of outputs.
Tensor data layouts for the outputs.
This argument can be a list that contains a distinct layout for each output. If the list has fewer than num_outputs elements, only the first outputs have the layout set and the rest of the outputs have no layout assigned.
preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.
seed (int, optional, default = -1) –
If not provided, it will be populated based on the global seed of the pipeline.