fix Operation.inputs value is null. #117

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -118,11 +118,17 @@ namespace Tensorflow
             name = name.EndsWith("/") ? ops._name_from_scope_name(name) : unique_name(name);
             var node_def = ops._NodeDef(op_type, name, device: "", attrs: attrs);
 
+            if (inputs == null)
+                inputs = new List<Tensor>();
+
+            var input_ops = inputs.Select(x => x.op).ToArray();
+            var control_inputs = _control_dependencies_for_inputs(input_ops);
+
             var op = new Operation(node_def, 
                 this,
                 inputs: inputs,
                 output_types: dtypes,
-                control_inputs: new object[] { },
+                control_inputs: control_inputs,
                 input_types: input_types,
                 original_op: null,
                 op_def: op_def);
@@ -131,6 +137,16 @@ namespace Tensorflow
             return op;
         }
 
+        /// <summary>
+        /// For an op that takes `input_ops` as inputs, compute control inputs.
+        /// </summary>
+        /// <param name="input_ops">The data input ops for an op to be created.</param>
+        /// <returns>A list of control inputs for the op to be created.</returns>
+        private Operation[] _control_dependencies_for_inputs(Operation[] input_ops)
+        {
+            return new Operation[0];
+        }
+
         private void _create_op_helper(Operation op, bool compute_device = true)
         {
 

src/TensorFlowNET.Core/Operations/Operation.cs

@@ -85,8 +85,42 @@ namespace Tensorflow
         }
 
         private Tensor[] _outputs;
-        public Tensor[] outputs => _outputs;
-        public Tensor[] inputs;
+        public Tensor[] outputs
+        {
+            get
+            {
+                if(_outputs == null)
+                {
+                    _outputs = new Tensor[NumOutputs];
+
+                    for (int i = 0; i < NumOutputs; i++)
+                        _outputs[i] = new Tensor(this, i, OutputType(i));
+                }
+
+                return _outputs;
+            }
+        }
+
+        private Tensor[] _inputs;
+        public Tensor[] inputs
+        {
+            get
+            {
+                if(_inputs == null)
+                {
+                    _inputs = new Tensor[NumInputs];
+
+                    for (int i = 0; i < NumInputs; i++)
+                    {
+                        var tf_outpus = Input(i);
+                        var op = new Operation(tf_outpus.oper);
+                        _inputs[i] = op.outputs[tf_outpus.index];
+                    }
+                }
+
+                return _inputs;
+            }
+        }
 
         public Operation(IntPtr handle)
         {
@@ -115,14 +149,10 @@ namespace Tensorflow
 
             _handle = ops._create_c_op(g, node_def, inputs);
 
-            _outputs = new Tensor[NumOutputs];
             output_types = new TF_DataType[NumOutputs];
 
             for (int i = 0; i < NumOutputs; i++)
-            {
                 output_types[i] = OutputType(i);
-                _outputs[i] = new Tensor(this, i, output_types[i]);
-            }
 
             Graph._add_op(this);
         }
@@ -131,8 +161,6 @@ namespace Tensorflow
         {
             AttrValue x = null;
 
-            var fields = new string[] { "s", "i", "f", "b", "Type", "Shape", "Tensor", "func" };
-
             using (var buf = new Buffer())
             {
                 c_api.TF_OperationGetAttrValueProto(_handle, name, buf, status);

src/TensorFlowNET.Core/Variables/gen_state_ops.py.cs

@@ -40,7 +40,7 @@ namespace Tensorflow
             _attrs["container"] = _op.get_attr<string>("container");
             _attrs["shared_name"] = _op.get_attr<string>("shared_name");
 
-            _execute.record_gradient("Placeholder", _inputs_flat, _attrs, _result, name);
+            _execute.record_gradient("VariableV2", _inputs_flat, _attrs, _result, name);
 
             return new Tensor(_op, 0, dtype);
         }
@@ -74,7 +74,7 @@ namespace Tensorflow
             _attrs["validate_shape"] = _op.get_attr<bool>("validate_shape");
             _attrs["use_locking"] = _op.get_attr<bool>("use_locking");
 
-            _execute.record_gradient("Placeholder", _inputs_flat, _attrs, _result, name);
+            _execute.record_gradient("Assign", _inputs_flat, _attrs, _result, name);
 
             return _result[0];
         }