class TensorDescriptor(ctypes.Structure)

Info	Value
Package	mvnc
Module	mvncapi
Version	2.0
See also	Graph, Fifo, GraphOption, FifoOption, Graph.get_option(), Fifo.get_option()

TensorDescriptor is a structure that describes graph inputs and outputs.

Field	Type	Description
n	int	The number of tensors in the batch. Only 1 currently supported.
c	int	The number of channels per tensor data element. For image tensors, this is the number of channels per pixel. For non-image tensors, this is always 1.
w	int	For image tensors, this is the width in pixels. For non-image tensors, this is always 1.
h	int	For image tensors, this is the height in pixels. For non-image tensors, this is always 1.
totalSize	int	The total size of the data. This is the number of bytes required to hold the entire tensor.
cStride	int	Stride (distance between elements in bytes) in the channel dimension.
wStride	int	Stride (distance between elements in bytes) in the horizontal dimension.
hStride	int	Stride (distance between elements in bytes) in the vertical dimension.
dataType	int	The tensor’s data type (FP16 or FP32).

Notes

To get a TensorDescriptor for Fifo allocation, you should use Graph.get_option() to get lists of input and output TensorDescriptors that are appropriate for the associated Graph.
If your application’s input tensor is not in a channel minor format (i.e. RGB/BGR), you can create a TensorDescriptor with appropriate values for the stride fields and pass it to Fifo.set_option() for FifoOption.RW_HOST_TENSOR_DESCRIPTOR. This currently cannot be used to perform scaling (n/c/h/w fields must match those in the FifoOption.RO_GRAPH_TENSOR_DESCRIPTOR for this Fifo). See the examples below.

Examples

Example 1: Get the input tensor descriptor list from a Graph.

import mvnc.mvncapi as mvnc

# Create and open a device and create and allocate a graph...

# Get a list of input TensorDescriptor objects from the graph
inputDescs = graph.get_option(mvnc.GraphOption.RO_INPUT_TENSOR_DESCRIPTORS)

...

Example 2: Create and set a channel-minor host tensor descriptor for an input Fifo.

import mvnc.mvncapi as mvnc

# Create and open a device and create and allocate a graph with fifos...

# The n/c/w/h fields for the RW_HOST_TENSOR_DESCRIPTOR must match the dimensions of the RO_GRAPH_TENSOR_DESCRIPTOR, so start with that
host_tensor_descriptor = fifoIn.get_option(mvnc.FifoOption.RO_GRAPH_TENSOR_DESCRIPTOR)

# Set the tensor data type
host_tensor_descriptor.dataType = mvnc.FifoDataType.FP32.value

# For channel-minor data with FP32 data type, there are 4 bytes between each element of the channel
# The horizontal stride (wStride), vertical stride (hStride), and totalSize can be calculated from there
host_tensor_descriptor.cStride = 4
host_tensor_descriptor.wStride = host_tensor_descriptor.cStride * host_tensor_descriptor.c
host_tensor_descriptor.hStride = host_tensor_descriptor.wStride * host_tensor_descriptor.w
host_tensor_descriptor.totalSize = host_tensor_descriptor.hStride * host_tensor_descriptor.h

# Set the option
fifoIn.set_option(mvnc.FifoOption.RW_HOST_TENSOR_DESCRIPTOR, host_tensor_descriptor)

...