public ModelDataset(IDatasetV2 input_dataset, AutotuneAlgorithm algorithm, long cpu_budget) : base(input_dataset) { variant_tensor = ops.model_dataset(input_dataset.variant_tensor, output_types, output_shapes, algorithm, cpu_budget); }
/// <summary> /// Identity transformation that models performance. /// </summary> /// <param name="input_dataset"></param> /// <param name="output_types"></param> /// <param name="output_shapes"></param> /// <param name="algorithm"></param> /// <param name="cpu_budget"></param> /// <param name="name"></param> /// <returns></returns> public Tensor model_dataset(Tensor input_dataset, TF_DataType[] output_types, TensorShape[] output_shapes, AutotuneAlgorithm algorithm, long cpu_budget, string name = null) => tf.Context.ExecuteOp("ModelDataset", name, new ExecuteOpArgs(input_dataset) .SetAttributes(new { algorithm, cpu_budget, output_types, output_shapes }));
/// <summary> /// Identity transformation that models performance. /// </summary> /// <param name="input_dataset"></param> /// <param name="output_types"></param> /// <param name="output_shapes"></param> /// <param name="algorithm"></param> /// <param name="cpu_budget"></param> /// <param name="name"></param> /// <returns></returns> public Tensor model_dataset(Tensor input_dataset, TF_DataType[] output_types, TensorShape[] output_shapes, AutotuneAlgorithm algorithm, long cpu_budget, string name = null) { if (tf.Context.executing_eagerly()) { var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName, "ModelDataset", name, null, input_dataset, "algorithm", algorithm, "cpu_budget", cpu_budget, "output_types", output_types, "output_shapes", output_shapes); return(results[0]); } throw new NotImplementedException(""); }
public IDatasetV2 model(AutotuneAlgorithm algorithm, long cpu_budget) => new ModelDataset(this, algorithm, cpu_budget);