Interface IWorker
Public interface for Workers. A worker is able to schedule models execution for a given backend.
Use WorkerFactory to instantiate a worker.
Syntax
public interface IWorker : IDisposable
Methods
Execute()
Non-blocking API that schedules network execution in one go
Remark: This API will only be non-blocking for GPU inference.
Declaration
Execute(IDictionary<String, Tensor>)
Non-blocking API that schedules network execution in one go, using the provider tensor dictionary for inputs.
Remark: This API will only be non-blocking for GPU inference.
Declaration
void Execute(IDictionary<string, Tensor> inputs)
Parameters
Execute(Tensor)
Non-blocking API that schedules network execution in one go, using the provider tensor as input.
Remark: This API will only be non-blocking for GPU inference.
Useful when network have only one input as input name is not needed.
Declaration
void Execute(Tensor input)
Parameters
| Type |
Name |
Description |
| Tensor |
input |
|
ExecuteAsync()
Non-blocking API that schedules network execution one layer at the time.
Remark: This API will only be non-blocking for GPU inference.
Check GetAsyncProgress() for progress.
Declaration
IEnumerator ExecuteAsync()
Returns
ExecuteAsync(IDictionary<String, Tensor>)
Non-blocking API that schedules network execution one layer at the time, using the provider tensor dictionary for inputs.
Remark: This API will only be non-blocking for GPU inference.
Check GetAsyncProgress() for progress.
Declaration
IEnumerator ExecuteAsync(IDictionary<string, Tensor> inputs)
Parameters
Returns
ExecuteAsync(Tensor)
Non-blocking API that schedules network execution one layer at the time, using the provider tensor as input.
Remark: This API will only be non-blocking for GPU inference.
Useful when network have only one input as input name is not needed.
Check GetAsyncProgress() for progress.
Declaration
IEnumerator ExecuteAsync(Tensor input)
Parameters
| Type |
Name |
Description |
| Tensor |
input |
|
Returns
GetAsyncProgress()
Progress of the scheduling, 0.0 = 0%, 1.0 = 100%
Declaration
Returns
PeekConstants(String)
Returns references to constants tensors for a layer. This reference might be valid only until the next Execute() or Dispose() method is called on the worker.
IMPORTANT: if you want tensor to outlive the worker, use CopyOutput() method or follow with TakeOwnership() call on the tensor, also worker Execute()
or PrepareForInput() should have been called at least once for the tensors to exist.
Declaration
Tensor[] PeekConstants(string layerName)
Parameters
| Type |
Name |
Description |
| String |
layerName |
|
Returns
PeekOutput()
Returns a reference to the first output tensor. This reference will be valid only until the next Execute() or Dispose() method is called on the worker.
Useful when network has only one output.
IMPORTANT: if you want tensor to outlive the worker, use CopyOutput() method or follow with TakeOwnership() call on the tensor.
Declaration
Returns
PeekOutput(String)
Returns a reference to output tensor by name. This reference will be valid only until the next Execute() or Dispose() method is called on the worker.
IMPORTANT: if you want tensor to outlive the worker, use CopyOutput() method or follow with TakeOwnership() call on the tensor.
Declaration
Tensor PeekOutput(string name)
Parameters
| Type |
Name |
Description |
| String |
name |
|
Returns
Optional method to prepare network for particular input dimensions
Declaration
void PrepareForInput(IDictionary<string, TensorShape> inputShapes)
Parameters
Specify tensor value for the named input of the network.
Declaration
void SetInput(string name, Tensor x)
Parameters
Specify single tensor value as the input for the network.
Useful when network has only one input and caller does not need to know input's name.
Declaration
Parameters
| Type |
Name |
Description |
| Tensor |
x |
|
Summary()
Returns a string summary after execution.
Declaration
Returns
WaitForCompletion()
Wait for completion of part of the network that was scheduled via ExecuteAsync()
Declaration
Extension Methods
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