holoscan::Tensor
holoscan::Tensor
Documentationholoscan::Tensor
Tensor class.
A Tensor is a multi-dimensional array of elements of a single data type.
The Tensor class is a wrapper around the DLManagedTensorContext struct that holds the DLManagedTensor object. (https://dmlc.github.io/dlpack/latest/c_api.html#c.DLManagedTensor).
This class provides a primary interface to access Tensor data and is interoperable with other frameworks that support DLManagedTensor.
Get a pointer to the underlying data.
Returns: The pointer to the Tensor’s data.
Get the device information of the Tensor.
Returns: The device information of the Tensor.
Get the Tensor’s data type information.
For details of the DLDataType struct see the DLPack documentation: https://dmlc.github.io/dlpack/latest/c_api.html#_CPPv410DLDataType
Returns: The DLDataType struct containing DLPack dtype information for the tensor.
Get the shape of the Tensor data.
Returns: The vector containing the Tensor’s shape.
Get the strides of the Tensor data.
Note that, unlike DLTensor.strides, the strides this method returns are in number of bytes, not elements (to be consistent with NumPy/CuPy’s strides).
Returns: The vector containing the Tensor’s strides.
Check if the tensor a has contiguous, row-major memory layout.
Returns: True if the tensor is contiguous, False otherwise.
Get the size (number of elements) in the Tensor.
The size is defined as the number of elements, not the number of bytes. For the latter, see ::nbytes.
If the underlying DLDataType contains multiple lanes, all lanes are considered as a single element. For example, a float4 vectorized type is counted as a single element, not four elements.
Returns: The size of the tensor in number of elements.
Get the number of dimensions of the Tensor.
Returns: The number of dimensions.
Get the itemsize of a single Tensor data element.
If the underlying DLDataType contains multiple lanes, itemsize takes this into account. For example, a Tensor containing (vectorized) float4 elements would have itemsize 16, not 4.
Returns: The itemsize of the Tensor’s data.
Get the total number of bytes for the Tensor’s data.
Returns: The size of the Tensor’s data in bytes.
Get a DLPack managed tensor pointer to the Tensor.
Returns: A DLManagedTensor* pointer corresponding to the Tensor.
Get a DLPack versioned managed tensor pointer to the Tensor.
Returns: A DLManagedTensorVersioned* pointer corresponding to the Tensor.
Get the internal DLManagedTensorContext of the Tensor.
Returns: A shared pointer to the Tensor’s DLManagedTensorContext.
Set the CUDA stream for stream-aware memory deallocation.
For sink operators that don’t emit data, this method should be called with the operator’s working CUDA stream to ensure allocators (like BlockMemoryPool) defer memory reuse until GPU operations on the stream complete. This prevents race conditions where memory is returned to the pool while GPU kernels are still reading from it.
This method only works for tensors whose memory is managed by a Holoscan/GXF allocator (i.e., tensors received from upstream operators in the pipeline). For tensors created from external sources via the DLPack interface (e.g., from CuPy or PyTorch), this method returns false and has no effect.
Returns: true if the stream was set successfully, false if the tensor’s memory is not managed by a Holoscan/GXF allocator.
Parameters
The CUDA stream that last accessed this tensor’s data.