gen_math_ops.floor_mod #160

src/TensorFlowNET.Core/Gradients/gradients_impl.py.cs

@@ -129,15 +129,23 @@ namespace Tensorflow
                             // for ops that do not have gradients.
                             var grad_fn = ops.get_gradient_function(op);
 
-                            Python.with<ops.name_scope>(new ops.name_scope(op.Name + "_grad"), delegate
+                            Python.with<ops.name_scope>(new ops.name_scope(op.Name + "_grad"), scope1 =>
                             {
+                                string name1 = scope1;
                                 if (grad_fn != null)
                                 {
                                     in_grads = _MaybeCompile(grad_scope, op, out_grads[0], null, grad_fn);
                                     _VerifyGeneratedGradients(in_grads, op);
                                 }
+
+                                if (gate_gradients)
+                                {
+
+                                }
                             });
-                            
+
+                            // temp fix name scope
+                            op.Graph._name_stack = "gradients";
                         }
                     }
                     else

src/TensorFlowNET.Core/Operations/OpDefLibrary.cs

@@ -93,6 +93,8 @@ namespace Tensorflow
                 foreach (var attr_def in op_def.Attr)
                 {
                     var key = attr_def.Name;
+                    if (!attrs.ContainsKey(key))
+                        Console.WriteLine($"{key} not found in attr_def.");
                     var value = attrs[key];
                     var attr_value = new AttrValue();
 

src/TensorFlowNET.Core/Operations/array_ops.py.cs

@@ -99,7 +99,7 @@ namespace Tensorflow
                     // result = gen_array_ops.shape();
                 }
 
-                return null;
+                return gen_array_ops.shape(input);
             });
         }
 

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -80,6 +80,12 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
+        public static Tensor shape(Tensor input, TF_DataType out_type = TF_DataType.TF_INT32, string name = "")
+        {
+            var _op = _op_def_lib._apply_op_helper("Shape", name, new { input, out_type });
+            return _op.outputs[0];
+        }
+
         public static Tensor size(Tensor input, TF_DataType out_type = TF_DataType.TF_INT32, string name = "")
         {
             var _op = _op_def_lib._apply_op_helper("Size", name, new { input, out_type });

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -45,6 +45,13 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
+        public static Tensor floor_mod(Tensor x, Tensor y, string name = "")
+        {
+            var _op = _op_def_lib._apply_op_helper("FloorMod", name, args: new { x, y });
+
+            return _op.outputs[0];
+        }
+
         /// <summary>
         /// Multiply the matrix "a" by the matrix "b".
         /// </summary>

src/TensorFlowNET.Core/Operations/math_ops.py.cs

@@ -19,6 +19,7 @@ namespace Tensorflow
 
             var input_rank = array_ops.size(input_shape);
             axes = (axes + input_rank) % input_rank;
+            var axes_shape = array_ops.shape(axes);
 
             return null;
         }

src/TensorFlowNET.Core/Tensors/Tensor.Operators.cs

@@ -79,7 +79,10 @@ namespace Tensorflow
 
         public static Tensor operator %(Tensor x, Tensor y)
         {
-            throw new NotImplementedException("math mod is not implemented");
+            return Python.with<ops.name_scope, Tensor>(new ops.name_scope("", "mod", new object[] { x, y }), scope =>
+            {
+                return gen_math_ops.floor_mod(x, y, scope);
+            });
         }
     }
 }

src/TensorFlowNET.Core/Tensors/TensorShape.cs

@@ -23,7 +23,7 @@ namespace Tensorflow
         /// <returns></returns>
         public bool is_fully_defined()
         {
-            return Dimensions != null && Dimensions.Count(x => x > 0) > 0;
+            return Dimensions != null && Dimensions.Count(x => x < 1) == 0;
         }
     }
 }