PipelineTensor
A PipelineTensor is a tensor that is bound to a Pipeline. It has the same lifecycle as the Pipeline it is subordinate to. Depending on whether it has local memory, it can categorized into two subclasses: PipelineTensorLocal or PipelineTensorPlaceholder. The former has local memory allocated to it, while the latter has no underlying memory, and works as a run-time reference.
Parameters
the pipeline in which the tensor is created.
whether the tensor should have local memory allocated inside the pipeline If true, the tensor is regarded as a pipeline local tensor; otherwise, a pipeline placeholder, which is accessible inside the pipeline, but must refer to a compatible global tensor when the pipeline is submitted for run.
the tensor's configuration.
See also
Throws
If the usage is not allowed by the SpatialML run-time Framework, or if the framework encounter internal error and cannot perform the requested behavior.
Inheritors
Functions
Create a slice using bracket operators from a tensor. This operator overload allows SpatialML framework users to apply tensors output from previous steps as a dynamic slices.
Create a slice using bracket operators from IntProgression. Different from the overloaded method that uses IntRange as inputs, IntProgression allows skip and backward iteration. Similarly, there must be the same number of IntProgression inputs as the number of this tensor's dimensions
Create a slice using bracket operators from IntRanges like 0..5, 1..2
Callback when the tensor resource is reset