Interpreter Class

Create a new tensorflow lite interpreter.

Create an interpreter from a flatbuffer model

Returns true if the object has been disposed.

Get the list of tensor index of the inputs tensors.

Get an array of all the input tensors

Get the number of ops in the model.

Get the list of tensor index of the outputs tensors.

Get an array of all the output tensors

Pointer to the unmanaged object

Get the number of tensors in the model.

Update allocations for all tensors. This will redim dependent tensors using the input tensor dimensionality as given. This is relatively expensive. If you know that your sizes are not changing, you need not call this.

Build the interpreter from a flatbuffer model

The dispose function that implements IDisposable interface

Release all the unmanaged memory associated with this interpreter

Determines whether the specified object is equal to the current object.

Destructor

Serves as the default hash function.

Get a tensor data structure.

Gets the Type of the current instance.

Invoke the interpreter (run the whole graph in dependency order).

Creates a shallow copy of the current Object.

Allow a delegate to look at the graph and modify the graph to handle parts of the graph themselves. After this is called, the graph may contain new nodes that replace 1 more nodes. WARNING: This is an experimental API and subject to change.

Release the managed resources. This function will be called during the disposal of the current object. override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object

Resize the input tensor

Set the number of threads available to the interpreter.

Returns a string that represents the current object.

A pointer to the unmanaged object