Note

Sentis is now called Inference Engine. The documentation has moved to https://docs.unity3d.com/Packages/com.unity.ai.inference@latest. Refer to the new location for the latest updates and guidance. Make sure to update your bookmarks and references accordingly.

Get output from a model

This section provides information on how to get the output from a model. To get intermediate tensors from layers other than the model outputs, refer to Get output from any layer.

Get the tensor output

To get the tensor output, you have two options: either use PeekOutput to get a reference to an output or CopyOutput to copy an output into a tensor that is owned outside of the scope of a worker.

The following sections provide information on the methods available for retrieving the tensor output, along with their respective strengths and weaknesses.

Use PeekOutput

Use PeekOutput to get a reference to the output of the tensor. PeekOutput returns a Tensor object so you usually need to cast it to a Tensor<float> or a Tensor<int>.

For example:

worker.Schedule(inputTensor);
Tensor<float> outputTensor = worker.PeekOutput() as Tensor<float>;
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Sentis worker memory allocator owns the reference returned by PeekOutput. It implies the following:

• You don't need to use Dispose on the output.
• If you change the output or you rerun the worker, both the worker output and the PeekOutput copy change.
• Using Dispose on the worker disposes the PeekOutput copy.

If you call Schedule again, the tensor is overwritten.

Note

Be careful when reading data from an output tensor, as in many instances, you might unintentionally trigger a blocking wait until the model finishes running before downloading the data from the graphics processing unit (GPU) or Burst to the central processing unit (CPU). To mitigate this overhead, consider reading output from a model asynchronously. Additionally, profiling a model can provide valuable insight into its performance.

Download the data of the original tensor

You can do a blocking download to a read only NativeArray or Array copy of the output tensor's data.

• Use DownloadToNativeArray on the tensor after you use PeekOutput.
• Use DownloadToArray on the tensor after you use PeekOutput.

Wait on the data of the original tensor

You can request a async readback of the output tensor data without interrupting the worker execution.

Tensor<float> outputTensor = worker.PeekOutput() as Tensor<float>;
var result = await outputTensor.ReadbackAndCloneAsync();
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Tensor<float> outputTensor = worker.PeekOutput() as Tensor<float>;
outputTensor.ReadbackRequest();

// when done
outputTensor.ReadbackAndClone(); // not blocking
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Refer to Read Outputs Asynchronously for details.

Use CopyOutput

You can copy a worker output into another tensor that is owned outside of the scope of a worker. If the tensor you pass in is null, Sentis will create a new tensor which is a copy of the worker's output. If the tensor is allready created, Sentis will reshape it to the correct size and copy the worker's output.

Tensor myOutputTensor;
//...
void Update () {
   worker.Schedule(inputTensor);
   worker.CopyOutput("output", ref myOutputTensor);
}
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CopyOutput reshapes the provided tensor to match calculated output shape. Ensure that the provided tensor has capacity for the output.

// The model outputs a tensor of shape (1, 10)

// CopyOutput works on empty tensors, i.e. tensors without a tensor data.
myOutputTensor = new Tensor<float>(new TensorShape(1, 10), data: null);
worker.CopyOutput("output", ref myOutputTensor);

// CopyOutputInto works on tensors of different shape as long as the dataOnBackend has large enough capacity
myOutputTensor = new Tensor<float>(new TensorShape(152));
worker.CopyOutput("output", ref myOutputTensor);
// myOutputTensor now has shape (1, 10) but still has dataOnBackend.maxCapacity == 152
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You are responsible for the tensor which output is copied into:

• You must Dispose of the tensor after you finish using it.
• The tensor isn't overwritten if you call Worker.Schedule again.

Multiple outputs

If the model has multiple outputs, you can use each output name as a parameter in Worker.PeekOutput.

Additional resources

• Manage memory
• Tensor fundamentals
• Use output data
• Read output from a model asynchronously
• Get output from any layer