Create and modify tensors

Tensor methods in Inference Engine are similar to methods found in frameworks like NumPy, TensorFlow, and PyTorch.

Create a tensor

You can create a basic tensor with the methods in the Tensor API.

For more information, refer to Create input for a model.

Get and set values of a tensor

If your tensor data backendType is BackendType.CPU and has finished being computed (IsReadbackRequestDone), you can directly set and get values.

var tensor = new Tensor<float>(new TensorShape(1, 2, 3));
tensor[0, 1, 2] = 5.2f; // set value at index 0 of dim0 = 1, index 1 of dim1 = 2 and index 2 of dim2 = 3

float value = tensor[0, 1, 2];
Assert.AreEqual(5.2f, value);

Reshape a tensor

You can reshape a tensor directly, for example:

var tensor = new Tensor<float>(new TensorShape(10));
tensor.Reshape(new TensorShape(2, 5));

The new shape of the tensor must fit in the allocated data on the backend. You can use the length property of a tensor shape and the maxCapacity property of the tensor data to check the number of elements.

var tensor = new Tensor<float>(new TensorShape(10));
Assert.AreEqual(10, tensor.count);
Assert.AreEqual(10, tensor.dataOnBackend.maxCapacity);

// Reshaping the tensor with a smaller shape

tensor.Reshape(new TensorShape(2, 3));
Assert.AreEqual(6, tensor.count);
Assert.AreEqual(10, tensor.dataOnBackend.maxCapacity);
// The underlying dataOnBackend still contains 10 elements

// reshape to match dataOnBackend.maxCapacity
tensor.Reshape(new TensorShape(1, 10));

When you reshape a tensor, Inference Engine doesn't modify the data or capacity of the underlying dataOnBackend.

Note

You can't reshape a tensor on the graphics processing unit (GPU) when using BackendType.GPUPixel because GPU textures aren't stored linearly.

Download values of a tensor

You can perform a blocking download to get a copy of the tensor data to a NativeArray or Array as follows:

var nativeArray = tensor.DownloadToNativeArray();
var array = tensor.DownloadToArray();

Note

These methods return copies of your tensor data. Any changes to the downloaded arrays don't affect the original tensor.

This download is a blocking call and will force a wait if ReadbackRequest hasn't been called or IsReadbackRequestDone is false. For more information, refer to Read Outputs Asynchronously.