public Func <Tensor, Tensor> to_graph(Func <Tensor, Tensor> func)
{
string func_name = $"{func.Method.Name}_{Guid.NewGuid()}";
var graph = new FuncGraph(func_name);
graph.as_default();
var input = tf.placeholder(tf.int32);
var output = func(input);
var opers = graph._nodes_by_name.Values.Select(x => x as Operation).ToArray();
graph.ToGraph(opers,
new[] { input },
new[] { output },
null);
graph.Exit();
return((Tensor input) =>
{
var result = tf.Runner.TFE_Execute(tf.Context,
tf.Context.DeviceName,
func_name,
new[] { input },
null,
1);
return result[0];
});
}
public Func <Tensor, Tensor, Tensor> to_graph(Func <Tensor, Tensor, Tensor> func)
{
string func_name = $"autograph_{Guid.NewGuid()}_{func.Method.Name}";
// IntPtr func_handle;
using (var graph = new FuncGraph(func_name))
{
var input1 = tf.placeholder(tf.int32);
var input2 = tf.placeholder(tf.int32);
var output = func(input1, input2);
var opers = graph._nodes_by_name.Values.Select(x => x as Operation).ToArray();
var func_handle = graph.ToGraph(opers,
new Operation[] { input1, input2 },
new Operation[] { output },
null);
}
return((Tensor a, Tensor b) =>
{
var result = tf.Runner.TFE_Execute(tf.Context,
tf.Context.DeviceName,
func_name,
new[] { a, b },
null,
1);
return result[0];
});
}
static void _copy_non_source(Operation op, FuncGraph graph, Dictionary <ITensorOrOperation, Operation> op_map, Graph base_graph)
{
Operation copied_op = null;
var copied_inputs = new Tensors();
tf_with(ops.control_dependencies(new object[] { op }), delegate
{
// Create a new op in the destination graph if it doesn't exist before.
var attrs = new Dictionary <string, AttrValue>();
foreach (var attr_def in op.node_def.Attr)
{
attrs[attr_def.Key] = attr_def.Value;
}
copied_op = graph.create_op(op.type,
copied_inputs,
dtypes: op.outputs.Select(x => x.dtype).ToArray(),
attrs: attrs,
name: op.name);
});
op_map[op] = copied_op;
foreach (var(i, o) in enumerate(op.outputs))
{
op_map[o] = copied_op.outputs[i];
}
}
public override void OnEntry(MethodExecutionArgs args)
{
func_name = $"autograph_{args.Instance.GetHashCode()}.{args.Method.Name}";
if (functions.ContainsKey(func_name))
{
if (args.Arguments[0] is Tensors tensor_inputs)
{
args.ReturnValue = functions[func_name](tensor_inputs.ToArray());
}
else
{
args.ReturnValue = functions[func_name](args.Arguments.Select(x => x as Tensor).ToArray());
}
args.FlowBehavior = FlowBehavior.Return;
return;
}
// make function as an Operation by autograph
graph = new FuncGraph(func_name);
// convert to Tensors
if (args.Arguments[0] is Tensors inputs)
{
originalInputs = inputs;
var new_inputs = inputs.Select(x => tf.placeholder(x.dtype, shape: x.TensorShape)).ToArray();
args.Arguments[0] = new Tensors(new_inputs);
}
else
{
originalInputs = new Tensors(args.Arguments.Length);
// convert args to placeholder
for (var i = 0; i < args.Arguments.Length; i++)
{
if (args.Arguments[i] is EagerTensor tensor)
{
originalInputs[i] = tensor;
args.Arguments[i] = tf.placeholder(tensor.dtype, shape: tensor.TensorShape);
}
}
}
}
static void _copy_source(Tensor s,
FuncGraph graph,
Dictionary <ITensorOrOperation, Operation> op_map,
bool handle_captures,
Dictionary <Tensor, Tensor> inverse_captures,
Graph base_graph)
{
Tensor copied_placeholder = null;
if (handle_captures && inverse_captures.ContainsKey(s))
{
copied_placeholder = graph.capture(inverse_captures[s], name: s.op.name);
}
else
{
throw new NotImplementedException("");
}
op_map[s] = copied_placeholder;
// Add an entry for the op of the source tensor so that if there are any nodes
// depending on that op via control dependencies it can work correctly.
op_map[s.op] = copied_placeholder.op;
}
/// <summary>
/// Copies the tensor and all its inputs recursively to the outer graph.
/// </summary>
/// <param name="tensors"></param>
/// <param name="graph"></param>
/// <param name="add_sources"></param>
/// <param name="handle_captures"></param>
/// <param name="base_graph"></param>
/// <returns></returns>
public static Dictionary <ITensorOrOperation, Operation> lift_to_graph(Tensors init_tensors,
FuncGraph graph,
List <Tensor> sources,
bool add_sources = false,
bool handle_captures = false,
Graph base_graph = null,
Dictionary <ITensorOrOperation, Operation> op_map = null)
{
base_graph = base_graph ?? init_tensors[0].graph;
op_map = op_map ?? new Dictionary <ITensorOrOperation, Operation>();
var visited_ops = sources.Select(x => x.op).ToList();
foreach (var init_tensor in init_tensors)
{
var src = map_subgraph(init_tensor, sources, visited_ops, add_sources);
sources.AddRange(src);
}
var ops_to_copy = new List <Operation>();
var marked_ops = new List <Operation>();
var ops_to_visit = new Stack <Operation>(init_tensors.Select(x => x.op));
var unvisited_ops = new List <Operation>(ops_to_visit.ToList());
while (unvisited_ops.Count > 0)
{
while (ops_to_visit.Count > 0)
{
var op = ops_to_visit.Pop();
if (marked_ops.Contains(op))
{
continue;
}
marked_ops.Add(op);
ops_to_copy.append(op);
foreach (var inp in op.inputs)
{
}
}
// difference_update
unvisited_ops.difference_update(marked_ops);
if (unvisited_ops.Count > 0)
{
ops_to_visit.Push(unvisited_ops.Last());
}
}
// When lifting from one FuncGraph to another, we will need to capture the
// relevant tensors as well.
var inverse_captures = new Dictionary <Tensor, Tensor>();
Tensor[] internal_captures = null;
if (base_graph is FuncGraph base_func_graph)
{
var captures = base_func_graph.captures;
foreach (var(external_capture, internal_capture) in captures)
{
inverse_captures[internal_capture] = external_capture;
}
internal_captures = base_func_graph.internal_captures;
}
graph.as_default();
var source_ops = new List <Operation>();
// Add the sources in the same order as the original graph.
foreach (var s in internal_captures)
{
if (sources.Contains(s))
{
sources.Remove(s);
source_ops.Add(s.op);
_copy_source(s: s,
graph: graph,
op_map: op_map,
handle_captures: handle_captures,
inverse_captures: inverse_captures,
base_graph: base_graph);
}
}
foreach (var op in reversed(ops_to_copy))
{
if (source_ops.Contains(op) || op_map.ContainsKey(op))
{
continue;
}
_copy_non_source(op, graph, op_map, base_graph);
}
graph.Exit();
return(op_map);
}