fix: RNN training error on linux.

src/TensorFlowNET.Core/APIs/c_api.cs

@@ -51,17 +51,13 @@ namespace Tensorflow
             return handle == IntPtr.Zero ? String.Empty : Marshal.PtrToStringAnsi(handle);
         }
 
-        public unsafe static byte[] ByteStringPiece(IntPtr handle)
+        public unsafe static byte[] ByteStringPiece(Buffer? handle)
         {
-            byte* str_data = (byte*)handle.ToPointer();
-            List<byte> bytes = new List<byte>();
-            byte current = 255;
-            while (current != ((byte)'\0'))
-            {
-                current = *(str_data++);
-                bytes.Add(current);
+            if(handle is null){
+                return new byte[0];
             }
-            return bytes.Take(bytes.Count - 1).ToArray();
+            var data = handle.ToArray();
+            return data;
         }
 
         [UnmanagedFunctionPointer(CallingConvention.Winapi)]

src/TensorFlowNET.Core/APIs/c_api.customize.cs

@@ -10,7 +10,7 @@ namespace Tensorflow
         [DllImport(TensorFlowLibName)]
         public static extern void TFC_SetAttr(SafeGraphHandle graph, IntPtr op, string attr_name, SafeBufferHandle attr_value_proto, SafeStatusHandle status);
         [DllImport(TensorFlowLibName)]
-        public static extern IntPtr TFC_GetHandleShapeAndType(SafeGraphHandle c_graph, TF_Output output);
+        public static extern SafeBufferHandle TFC_GetHandleShapeAndType(SafeGraphHandle c_graph, TF_Output output);
         [DllImport(TensorFlowLibName)]
         public static extern void TFC_SetHandleShapeAndType(SafeGraphHandle c_graph, TF_Output output, byte[] data, long proto_len, SafeStatusHandle status);
     }

src/TensorFlowNET.Core/Eager/GraphOnlyOps.cs

@@ -0,0 +1,25 @@
+using Tensorflow;
+
+internal static class GraphOnlyOps
+{
+    /// <summary>
+    /// Graph-only version of tf.compat.v1.placeholder(), for internal use only.
+    /// </summary>
+    /// <param name="dtyype"></param>
+    /// <param name="shape"></param>
+    /// <param name="name"></param>
+    /// <returns></returns>
+    internal static Tensor graph_placeholder(TF_DataType dtype, Shape shape, string? name = null)
+    {
+        var dtype_value = new AttrValue() { Type = dtype.as_datatype_enum() };
+        var shape_value = new AttrValue() { Shape = shape.as_proto() };
+        var g = ops.get_default_graph();
+        Dictionary<string, AttrValue> attrs = new();
+        attrs["dtype"] = dtype_value;
+        attrs["shape"] = shape_value;
+        var op = g.create_op("Placeholder", new Tensor[0], new TF_DataType[] { dtype },
+            new TF_DataType[0], attrs: attrs, name: name);
+        var result = op.outputs[0];
+        return result;
+    }
+}

src/TensorFlowNET.Core/Graphs/FuncGraph.cs

@@ -544,12 +544,12 @@ public class FuncGraph : Graph, IDisposable
             Tensor placeholder;
             try
             {
-                placeholder = tf.placeholder(tensor.dtype, tensor.shape, name);
+                placeholder = GraphOnlyOps.graph_placeholder(tensor.dtype, tensor.shape, name);
             }
-            catch (ValueError)
+            catch (ValueError ex)
             {
-                // TODO(Rinne): Add warning here.
-                placeholder = tf.placeholder(tensor.dtype, tensor.shape);
+                tf.Logger.Warning(ex.ToString());
+                placeholder = GraphOnlyOps.graph_placeholder(tensor.dtype, tensor.shape);
             }
             handle_data_util.copy_handle_data(tensor, placeholder);
             if (name is not null)
@@ -575,12 +575,12 @@ public class FuncGraph : Graph, IDisposable
             Tensor placeholder;
             try
             {
-                placeholder = tf.placeholder(spec.dtype, spec.shape, requested_name);
+                placeholder = GraphOnlyOps.graph_placeholder(spec.dtype, spec.shape, requested_name);
             }
             catch (ValueError)
             {
                 // TODO(Rinne): Add warning here.
-                placeholder = tf.placeholder(spec.dtype, spec.shape);
+                placeholder = GraphOnlyOps.graph_placeholder(spec.dtype, spec.shape);
             }
             if (name is not null)
             {

src/TensorFlowNET.Core/Operations/list_ops.cs

@@ -31,7 +31,7 @@ namespace Tensorflow.Operations
             }
             else
             {
-                return ops.convert_to_tensor(shape);
+                return ops.convert_to_tensor(shape, dtype: dtypes.int32);
             }
         }
 

src/TensorFlowNET.Core/Operations/while_v2.cs

@@ -38,9 +38,9 @@ namespace Tensorflow.Operations
             int len_orig_loop_vars = orig_loop_vars.Length;
 
             loop_vars = _tensor_array_to_flow(loop_vars);
-            loop_vars = Nest.MapStructure(x => _convert_to_tensor_or_indexed_slices(x, TF_DataType.DtInvalid, null), loop_vars).ToTensors();
+            loop_vars = Nest.MapStructure(x => _convert_to_tensor_or_indexed_slices(x), loop_vars).ToTensors();
 
-            var loop_vars_signature = Nest.MapStructure(x => new TensorSpec(x.shape, x.dtype), _tensor_array_to_flow(loop_vars));
+            var loop_vars_signature = Nest.MapStructure(x => new TensorSpec(x.shape, x.dtype), loop_vars);
 
             var flat_shape_invariants = Nest.Flatten(loop_vars_signature).Select(x => x.shape).ToArray();
 
@@ -379,10 +379,9 @@ namespace Tensorflow.Operations
             return cond_graph.unique_name(cond_graph.Name + "___redundant_placeholder");
         }
 
-        private static Tensor _convert_to_tensor_or_indexed_slices(Tensor value, TF_DataType dtype, 
-            string name)
+        private static Tensor _convert_to_tensor_or_indexed_slices(Tensor value)
         {
-            return ops.convert_to_tensor(value, dtype, name, false);
+            return ops.convert_to_tensor(value, as_ref: false);
         }
 
         private static Tensor _build_maximum_iterations_loop_var(int maximum_iterations = -1)

src/TensorFlowNET.Core/ops.cs

@@ -576,7 +576,8 @@ namespace Tensorflow
         public static HandleData get_resource_handle_data(Tensor graph_op)
         {
             var handle_data = c_api.TFC_GetHandleShapeAndType(graph_op.graph.c_graph, graph_op._as_tf_output());
-            return HandleData.Parser.ParseFrom(c_api.ByteStringPiece(handle_data));
+            var handle_str = c_api.ByteStringPiece(handle_data.DangerousGetHandle() == IntPtr.Zero ? null : new Buffer(handle_data));
+            return HandleData.Parser.ParseFrom(handle_str);
         }
 
         public static void dismantle_graph(Graph graph)