public override List <Tensor> Call(List <Array> inputs)
{
var feed_dict = new Dictionary <Tensor, Array>();
if (this.inputs != null && this.inputs.Count > 0)
{
foreach (var tuple in Enumerable.Zip(this.inputs, inputs, (a, b) => Tuple.Create(a, b)))
{
// if (is_sparse(tensor))
// {
// sparse_coo = value.tocoo()
// indices = np.concatenate((np.expand_dims(sparse_coo.row, 1),
// np.expand_dims(sparse_coo.col, 1)), 1)
// value = (indices, sparse_coo.data, sparse_coo.shape)
// }
feed_dict[tuple.Item1] = tuple.Item2;
}
}
var session = backend.Session;
var init = graph.GetGlobalVariablesInitializer();
if (init.Length > 0)
{
Debug.Log("Initializing variables in function" + name + " call.");
foreach (var op in init)
{
//Debug.Log(" - " + op.Name);
session.Run(new TFOutput[0], new TFTensor[0], new TFOutput[0], new[] { op });
}
Debug.Log("Initializing variables in function" + name + " done.");
//Debug.Log("Operations:");
//foreach (var op in graph.GetEnumerator())
// Debug.Log(" - " + op.Name);
}
//Console.WriteLine("Before:");
//PrintVariables(feed_dict, session);
// Console.ReadKey();
var runner = session.GetRunner();
if (this.outputs != null)
{
foreach (var o in this.outputs)
{
runner.Fetch(backend.In(o).Output);
}
}
if (this.updates_op != null)
{
foreach (var op in this.updates_op)
{
runner.AddTarget(op);
}
}
List <TFTensor> tensors = new List <TFTensor>();
foreach (KeyValuePair <Tensor, Array> pair in feed_dict)
{
UnityTFTensor t = backend.In(pair.Key);
//get the shape based on the tensor and input data length
TFTensor data = null;
if (t.TF_Shape == null || t.TF_Shape.Length == 0)
{
Debug.Assert(pair.Value.Length == 1, "Input tensor is a scalar but feed data has more than 1 data");
data = UnityTFUtils.TFTensorFromT(pair.Value);
}
else
{
long[] actualShape = t.TF_Shape.Copy();
int totalLength = Mathf.Abs((int)actualShape.Aggregate((s, n) => n * s));
int indexOfBatch = actualShape.IndexOf(-1);
if (indexOfBatch >= 0)
{
actualShape[indexOfBatch] = pair.Value.Length / totalLength;
}
Debug.Assert(totalLength <= pair.Value.Length, "Feed array does not have enough data");
//Debug.Log("totalLength:"+totalLength + " Shape:" + string.Join(",", actualShape));
//TFTensor data = TFTensor.FromBuffer(new TFShape(actualShape), (dynamic)pair.Value, 0, totalLength *(pair.Value.Length / totalLength));
data = UnityTFUtils.TFTensorFromArray(pair.Value, new TFShape(actualShape));
}
tensors.Add(data);
runner.AddInput(t.Output, data);
}
var updated = runner.Run();
foreach (var d in tensors)
{
d.Dispose();
}
//Console.WriteLine();
//foreach (var v in updated)
//{
// object obj = v.GetValue();
// if (obj is float[,])
// Console.WriteLine((obj as float[,]).ToCSharp());
// else if (obj is float[])
// Console.WriteLine((obj as float[]).ToCSharp());
// else
// Console.WriteLine(obj);
//}
//Console.WriteLine();
//Console.WriteLine();
//Console.WriteLine("After:");
//PrintVariables(feed_dict, session);
if (updated != null && updated.Length > 0)
{
return(updated.Get(0, this.outputs.Count).Select(t =>
{
var result = new UnityTFTensor(backend);
result.TensorValue = t.GetValue();
result.TensorType = t.TensorType;
return (Tensor)result;
}).ToList());
}
else
{
return(null);
}
}
private void PrintVariables(Dictionary <Tensor, Array> feed_dict, TFSession session)
{
string[] ops =
{
//"SGD/grad/dense_1/dense_1/kernel/var",
//"SGD/grad/dense_2/dense_2/kernel/var",
//"SGD/grad/dense_2/dense_2/bias/var",
//"loss/dense_1_loss/y_true",
//"loss/dense_1_loss/y_pred",
//"loss/dense_1_loss/weights",
//"iterations/var",
//"lr/var",
//"lr_t",
//"p_t",
//"metrics/binary_accuracy/Round0",
//"metrics/binary_accuracy/Cast0",
//"metrics/binary_accuracy/Mean0",
//"metrics/binary_accuracy/Equal0",
//"metrics/binary_accuracy/value",
//"metrics/score_array/mean"
//"beta_1/var",
//"beta_2/var",
//"decay/var",
//"adam/grad/dense_1/dense_1/kernel/var",
//"dense_1/variance_scaling/1/scaled",
//"dense_1/dense_1/kernel/var",
//"dense_1/call/dot",
//"dense_1/call/Sigmoid0",
};
foreach (var op in ops)
{
try
{
var debugRunner = session.GetRunner();
foreach (KeyValuePair <Tensor, Array> pair in feed_dict)
{
UnityTFTensor t = backend.In(pair.Key);
debugRunner.AddInput(t.Output, pair.Value);
}
Console.WriteLine(op);
debugRunner.Fetch(op);
var v = debugRunner.Run();
object obj = v[0].GetValue();
foreach (var va in v)
{
va.Dispose();
}
if (obj is float[, ])
{
Console.WriteLine((obj as float[, ]).ToCSharp());
}
else if (obj is float[])
{
Console.WriteLine((obj as float[]).ToCSharp());
}
else if (obj is bool[, ])
{
Console.WriteLine((obj as bool[, ]).ToCSharp());
}
else if (obj is bool[])
{
Console.WriteLine((obj as bool[]).ToCSharp());
}
else if (obj is sbyte[, ])
{
Console.WriteLine((obj as sbyte[, ]).ToCSharp());
}
else if (obj is sbyte[])
{
Console.WriteLine((obj as sbyte[]).ToCSharp());
}
else
{
Console.WriteLine(obj);
}
}
catch
{
}
}
}
