fix dtypes.as_numpy_datatype for bool

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

@@ -16,14 +16,16 @@ namespace Tensorflow
                 name = scope;
                 var xs = ops.convert_n_to_tensor(data);
                 condition = ops.convert_to_tensor(condition, name: "Condition");
-                Func<Operation[]> true_assert = () => new Operation[]
+                Func<Operation[]> true_assert = () =>
                 {
-                    gen_logging_ops._assert(condition, data, summarize, name: "Assert")
+                    var assert = gen_logging_ops._assert(condition, data, summarize, name: "Assert");
+                    return new Operation[] { assert };
                 };
 
-                Func<Operation[]> false_assert = () => new Operation[]
+                Func<Operation[]> false_assert = () =>
                 {
-                    gen_control_flow_ops.no_op()
+                    var op = gen_control_flow_ops.no_op();
+                    return new Operation[] { op };
                 };
 
                 var guarded_assert = cond(condition, false_assert, true_assert, name: "AssertGuard");

src/TensorFlowNET.Core/Tensors/dtypes.cs

@@ -10,6 +10,8 @@ namespace Tensorflow
         {
             switch (type)
             {
+                case TF_DataType.TF_BOOL:
+                    return typeof(bool);
                 case TF_DataType.TF_INT32:
                     return typeof(int);
                 case TF_DataType.TF_INT16:

src/TensorFlowNET.Core/Tensors/tensor_util.cs

@@ -47,16 +47,23 @@ namespace Tensorflow
             var tensor_dtype =  tensor.Dtype.as_numpy_dtype();
 
             if (tensor.TensorContent.Length > 0)
-                return np.frombuffer(tensor.TensorContent.ToByteArray(), tensor_dtype)
-                    .reshape(shape);
+            {
+                return np.frombuffer(tensor.TensorContent.ToByteArray(), tensor_dtype).reshape(shape);
+            }
             else if (tensor.Dtype == DataType.DtHalf || tensor.Dtype == DataType.DtBfloat16)
                 ;
             else if (tensor.Dtype == DataType.DtFloat)
                 ;
             else if (new DataType[] { DataType.DtInt32, DataType.DtUint8 }.Contains(tensor.Dtype))
+            {
                 if (tensor.IntVal.Count == 1)
-                    return np.repeat(np.array(tensor.IntVal[0]), Convert.ToInt32(num_elements))
-                        .reshape(shape);
+                    return np.repeat(np.array(tensor.IntVal[0]), num_elements).reshape(shape);
+            }
+            else if (tensor.Dtype == DataType.DtBool)
+            {
+                if (tensor.BoolVal.Count == 1)
+                    return np.repeat(np.array(tensor.BoolVal[0]), num_elements).reshape(shape);
+            }
 
             throw new NotImplementedException("MakeNdarray");
         }