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);
