/// <summary>
/// Creates an `Operation`.
/// </summary>
/// <param name="node_def">`node_def_pb2.NodeDef`. `NodeDef` for the `Operation`.</param>
/// <param name="g">`Graph`. The parent graph.</param>
/// <param name="inputs">list of `Tensor` objects. The inputs to this `Operation`.</param>
/// <param name="output_types">list of `DType` objects.</param>
/// <param name="control_inputs">
/// list of operations or tensors from which to have a
/// control dependency.
/// </param>
/// <param name="input_types">
/// List of `DType` objects representing the
/// types of the tensors accepted by the `Operation`. By default
/// uses `[x.dtype.base_dtype for x in inputs]`. Operations that expect
/// reference-typed inputs must specify these explicitly.
/// </param>
/// <param name="original_op"></param>
/// <param name="op_def"></param>
public Operation(NodeDef node_def, Graph g, Tensor[] inputs = null, TF_DataType[] output_types = null, ITensorOrOperation[] control_inputs = null, TF_DataType[] input_types = null, string original_op = "", OpDef op_def = null)
{
graph = g;
// Build the list of control inputs.
var control_input_ops = new List <Operation>();
if (control_inputs != null)
{
foreach (var c in control_inputs)
{
switch (c)
{
case Operation c1:
control_input_ops.Add(c1);
break;
default:
throw new NotImplementedException($"Control input must be an Operation, a Tensor, or IndexedSlices: {c}");
}
}
}
// This will be set by self.inputs.
_id_value = graph._next_id();
if (op_def == null)
{
op_def = g.GetOpDef(node_def.Op);
}
var grouped_inputs = _reconstruct_sequence_inputs(op_def, inputs, node_def.Attr);
_handle = ops._create_c_op(g, node_def, grouped_inputs, control_input_ops.ToArray());
// Initialize self._outputs.
output_types = new TF_DataType[NumOutputs];
for (int i = 0; i < NumOutputs; i++)
{
output_types[i] = OutputType(i);
}
_outputs = new Tensor[NumOutputs];
for (int i = 0; i < NumOutputs; i++)
{
_outputs[i] = new Tensor(this, i, OutputType(i));
}
graph._add_op(this);
if (_handle != IntPtr.Zero)
{
_control_flow_post_processing();
}
}
public Operation(NodeDef node_def, Graph g, List <Tensor> inputs = null, TF_DataType[] output_types = null, object control_inputs = null, TF_DataType[] input_types = null, string original_op = "", OpDef op_def = null)
{
_graph = g;
_id_value = _graph._next_id();
_c_op = ops._create_c_op(g, node_def, inputs);
var num_outputs = c_api.TF_OperationNumOutputs(_c_op);
_outputs = new Tensor[num_outputs];
for (int i = 0; i < num_outputs; i++)
{
_outputs[i] = new Tensor(this, i, TF_DataType.TF_FLOAT);
}
_graph._add_op(this);
}
public Operation(NodeDef node_def, Graph g, List <Tensor> inputs = null, TF_DataType[] output_types = null, object control_inputs = null, TF_DataType[] input_types = null, string original_op = "", OpDef op_def = null)
{
Graph = g;
_id_value = Graph._next_id();
if (op_def == null)
{
op_def = g.GetOpDef(node_def.Op);
}
_handle = ops._create_c_op(g, node_def, inputs);
output_types = new TF_DataType[NumOutputs];
for (int i = 0; i < NumOutputs; i++)
{
output_types[i] = OutputType(i);
}
Graph._add_op(this);
}
