Method _executeAsync

tfjs-converter/src/executor/graph_executor.ts:458–515

* Executes the inference for given input tensors in Async fashion. * @param inputs Tensor map for the model inputs, keyed by the input node * names. * @param outputs Optional. output node name from the Tensorflow model, * if no outputs are specified, the default outputs of the model woul

(
      inputs: NamedTensorMap, outputs?: string[], isFunctionExecution = false,
      tensorArrayMap: TensorArrayMap = {},
      tensorListMap: TensorListMap = {})

   * function execution.
   */
  private async _executeAsync(
      inputs: NamedTensorMap, outputs?: string[], isFunctionExecution = false,
      tensorArrayMap: TensorArrayMap = {},
      tensorListMap: TensorListMap = {}): Promise<Tensor[]> {
    // Dispose any tensors from a prior run to avoid leaking them.
    this.disposeIntermediateTensors();
    if (!isFunctionExecution) {
      inputs = this.mapInputs(inputs);
      this.checkInputs(inputs);
      this.checkInputShapeAndType(inputs);
      outputs = this.mapOutputs(outputs);
      this.checkOutputs(outputs);
    }

    // Keep tensors if KEEP_INTERMEDIATE_TENSORS is on.
    try {
      this.keepIntermediateTensors = env().getBool('KEEP_INTERMEDIATE_TENSORS');
    } catch (e) {
      this.keepIntermediateTensors = false;
      console.warn(e.message);
    }

    const context = new ExecutionContext(
        this.weightMap, tensorArrayMap, tensorListMap, this.functionExecutorMap,
        this.parseNodeNameCache);

    if (this.keepIntermediateTensors) {
      this.clonedTensorsMap = this.cloneTensorMap(this.weightMap);
    }

    // Graph with control flow op requires runtime evaluation of the execution
    // order, while without control flow the execution order is pre-determined
    // in the compile method.
    const tensorsMap = await this.executeWithControlFlow(
        inputs, context, outputs, isFunctionExecution);
    const results = outputs.map(name => getTensor(name, tensorsMap, context));

    // dispose all the intermediate tensors
    const outputIds = results.map(t => t.id);
    const inputIds = Object.keys(inputs).map(name => inputs[name].id);
    const keepIds =
        new Set<number>([...outputIds, ...inputIds, ...this.weightIds]);

    Object.values(tensorsMap).forEach(tensorsList => {
      tensorsList.forEach(tensor => {
        if (tensor && !tensor.isDisposed && !keepIds.has(tensor.id)) {
          tensor.dispose();
        }
      });
    });

    // dispose the context for the root executor
    if (this.parent == null) {
      context.dispose(keepIds);
    }

    return results;
  }