CheckInputFromValidContext

src/TensorFlowNET.Core/Operations/NnOps/rnn.cs

@@ -172,7 +172,8 @@ namespace Tensorflow.Operations
 
                 for (int i = 0; i < input_ta.Count; i++)
                 {
-                    var (ta, input_) = (input_ta[0], flat_input[0]);
+                    var (ta, input_) = (input_ta[i], flat_input[i]);
+                    ta.unstack(input_);
                 }
             }
 
@@ -185,16 +186,16 @@ namespace Tensorflow.Operations
 
             Func<BodyItemInRnnWhileLoop, Tensor> cond = (item) =>
             {
-                return time < loop_bound;
+                return item.time < loop_bound;
             };
 
             // Take a time step of the dynamic RNN.
             Func<BodyItemInRnnWhileLoop, BodyItemInRnnWhileLoop> _time_step = (item) =>
             {
-                return item;
+                throw new NotImplementedException("");
             };
 
-            control_flow_ops.while_loop<BodyItemInRnnWhileLoop>(
+            control_flow_ops.while_loop(
               cond: cond,
               body: _time_step,
               loop_vars: new BodyItemInRnnWhileLoop(time, output_ta.ToArray(), state),

src/TensorFlowNET.Core/Operations/Operation.Control.cs

@@ -30,10 +30,9 @@ namespace Tensorflow
         /// </summary>
         public void _control_flow_post_processing()
         {
-            foreach(var input_tensor in inputs)
+            foreach(Tensor input_tensor in inputs)
             {
-                //TODO: implement below code dependency
-                //control_flow_util.CheckInputFromValidContext(this, input_tensor.op);
+                control_flow_util.CheckInputFromValidContext(this, input_tensor.op);
             }
 
             if (_control_flow_context != null)

src/TensorFlowNET.Core/Operations/Operation.cs

@@ -23,6 +23,7 @@ using System.Collections.Generic;
 using System.IO;
 using System.Linq;
 using Tensorflow.Util;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Operations/_GraphTensorArray.cs

@@ -25,6 +25,7 @@ namespace Tensorflow.Operations
     internal class _GraphTensorArray
     {
         internal TF_DataType _dtype;
+        public TF_DataType dtype => _dtype;
 
         /// <summary>
         /// Used to keep track of what tensors the TensorArray should be
@@ -32,14 +33,17 @@ namespace Tensorflow.Operations
         /// first tensor written to it.
         /// </summary>
         bool _colocate_with_first_write_call;
+        public bool colocate_with_first_write_call => _colocate_with_first_write_call;
 
         bool _infer_shape;
-        bool _dynamic_size;
-        List<TensorShape> _element_shape;
+        public bool infer_shape => _infer_shape;
+        public bool _dynamic_size;
+        public List<TensorShape> _element_shape;
 
-        List<Tensor> _colocate_with;
+        public List<Tensor> _colocate_with;
 
         internal Tensor _handle;
+        public Tensor handle => _handle;
         internal Tensor _flow;
 
         public _GraphTensorArray(TF_DataType dtype, Tensor size, bool? dynamic_size = null,

src/TensorFlowNET.Core/Operations/control_flow_ops.cs

@@ -21,6 +21,7 @@ using Tensorflow.Operations;
 using Tensorflow.Operations.ControlFlows;
 using util = Tensorflow.control_flow_util;
 using static Tensorflow.Binding;
+using Tensorflow.Util;
 
 namespace Tensorflow
 {
@@ -251,12 +252,16 @@ namespace Tensorflow
                 return gen_array_ops.identity(data, name: name);
         }
 
-        public static void _SetShapeInvariants(Tensor[] input_vars, Tensor[] enter_vars, TensorShape shapes = null)
+        public static void _SetShapeInvariants(Tensor[] input_vars, Tensor[] enter_vars, TensorShape[] shapes = null)
         {
             if (shapes == null)
                 return;
 
-            throw new NotImplementedException("_SetShapeInvariants");
+            var flat_shapes = nest.flatten2(shapes);
+            foreach (var (inp, var, shape) in zip(input_vars, enter_vars, flat_shapes))
+            {
+                var.set_shape(shape);
+            }
         }
 
         ///  <summary>
@@ -428,12 +433,12 @@ namespace Tensorflow
                     .Select(pair => merge(new Tensor[] { pair.Item1, pair.Item2 }))
                     .ToArray();
 
-                merges = _convert_flows_to_tensorarrays(new Tensor[] { (Tensor)orig_res_t }, merges);
+                var merges2 = _convert_flows_to_tensorarrays(new ITensorOrTensorArray[] { (Tensor)orig_res_t }, merges);
 
                 ops.add_to_collection(tf.GraphKeys.COND_CONTEXT, context_t);
                 ops.add_to_collection(tf.GraphKeys.COND_CONTEXT, context_f);
 
-                return merges[0];
+                return new Tensor(IntPtr.Zero);
             });
         }
 
@@ -473,22 +478,28 @@ namespace Tensorflow
                 var res_f_flat = res_f;
 
                 var merges = zip(res_f_flat, res_t_flat)
-                    .Select(pair => merge(new Tensor[] { pair.Item1, pair.Item2 }))
+                    .Select(pair => merge(new [] { pair.Item1, pair.Item2 }))
                     .ToArray();
 
-                merges = _convert_flows_to_tensorarrays(orig_res_t, merges);
+                var merges2 = _convert_flows_to_tensorarrays(orig_res_t.Select(x => (ITensorOrTensorArray)x).ToArray(), merges);
 
                 ops.add_to_collection(tf.GraphKeys.COND_CONTEXT, context_t);
                 ops.add_to_collection(tf.GraphKeys.COND_CONTEXT, context_f);
 
-                return merges;
+                return new[] { new Tensor(IntPtr.Zero) };
             });
         }
 
-        public static Tensor[] _convert_flows_to_tensorarrays<T>(T tensors_or_tensorarrays, Tensor[] tensors_or_flows)
+        public static ITensorOrTensorArray[] _convert_flows_to_tensorarrays(ITensorOrTensorArray[] tensors_or_tensorarrays, Tensor[] tensors_or_flows)
         {
-            // zip(tensors_or_tensorarrays, tensors_or_flows).Select((ta, t_or_flow) => ta).ToArray();
-            return tensors_or_flows;
+            return zip(tensors_or_tensorarrays, tensors_or_flows).Select(x =>
+            {
+                var (ta, t_or_flow) = (x.Item1, x.Item2);
+                if (ta is TensorArray ta_1)
+                    return tensor_array_ops.build_ta_with_new_flow(ta_1, t_or_flow) as ITensorOrTensorArray;
+                else
+                    return t_or_flow as ITensorOrTensorArray;
+            }).ToArray();
         }
 
         /// <summary>
@@ -592,7 +603,7 @@ namespace Tensorflow
         /// <param name="loop_vars"></param>
         /// <param name="i"></param>
         public static Tensor while_loop<TItem>(Func<TItem, Tensor> cond, Func<TItem, TItem> body, TItem loop_vars,
-            TensorShape shape_invariants = null,
+            TensorShape[] shape_invariants = null,
             int parallel_iterations = 10,
             bool back_prop = true,
             bool swap_memory = false,
@@ -617,8 +628,8 @@ namespace Tensorflow
                 var orig_body = body;
 
                 LoopVar<TItem> loop_vars_1 = null;
-                Func<Tensor, TItem, LoopVar<TItem>> body_buildloop = null;
-                Func<Tensor, TItem, Tensor> cond_buildloop = null;
+                Func<LoopVar<TItem>, LoopVar<TItem>> body_buildloop = null;
+                Func<LoopVar<TItem>, Tensor> cond_buildloop = null;
 
                 if (try_to_pack)
                 {
@@ -627,9 +638,18 @@ namespace Tensorflow
                 else
                 {
                     loop_vars_1 = new LoopVar<TItem>(counter, loop_vars);
-                    cond_buildloop = (i, lv) => 
-                            math_ops.logical_and(i < maximum_iterations, orig_cond(lv));
-                    body_buildloop = (i, lv) => new LoopVar<TItem>(i + 1, orig_body(lv));
+                    cond_buildloop = (item) =>
+                    {
+                        var (i, lv) = (item.Counter, item.Item);
+                        var oc = orig_cond(lv);
+                        return math_ops.logical_and(i < maximum_iterations, oc);
+                    };
+
+                    body_buildloop = (item) =>
+                    {
+                        var (i, lv) = (item.Counter, item.Item);
+                        return new LoopVar<TItem>(i + 1, orig_body(lv));
+                    };
                 }
                 try_to_pack = false;
 

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

@@ -14,7 +14,9 @@
    limitations under the License.
 ******************************************************************************/
 
+using System;
 using Tensorflow.Operations;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -53,5 +55,25 @@ namespace Tensorflow
                 ctxt = ctxt.outer_context;
             return ctxt;
         }
+
+        public static void CheckInputFromValidContext(Operation op, Operation input_op)
+        {
+            var op_ctxt = op._get_control_flow_context();
+            var input_ctxt = GetOutputContext(input_op);
+            var valid = false;
+            if (input_ctxt == null)
+                valid = true;
+            else if (op_ctxt == input_ctxt)
+                valid = true;
+            else
+            {
+                throw new NotImplementedException("");
+            }
+
+            if (!valid)
+            {
+                throw new NotImplementedException("");
+            }
+        }
     }
 }

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -14,6 +14,8 @@
    limitations under the License.
 ******************************************************************************/
 
+using static Tensorflow.Binding;
+
 namespace Tensorflow
 {
     public static class gen_math_ops

src/TensorFlowNET.Core/Operations/tensor_array_ops.cs

@@ -0,0 +1,33 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public class tensor_array_ops
+    {
+        /// <summary>
+        /// Builds a TensorArray with a new `flow` tensor.
+        /// </summary>
+        /// <param name="old_ta"></param>
+        /// <param name="flow"></param>
+        /// <returns></returns>
+        public static TensorArray build_ta_with_new_flow(TensorArray old_ta, Tensor flow)
+        {
+            var impl = old_ta._implementation;
+
+            var new_ta = new TensorArray(
+                dtype: impl.dtype,
+                handle: impl.handle,
+                flow: flow,
+                infer_shape: impl.infer_shape,
+                colocate_with_first_write_call: impl.colocate_with_first_write_call);
+
+            var new_impl = new_ta._implementation;
+            new_impl._dynamic_size = impl._dynamic_size;
+            new_impl._colocate_with = impl._colocate_with;
+            new_impl._element_shape = impl._element_shape;
+            return new_ta;
+        }
+    }
+}

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -20,7 +20,8 @@ Building, training and infering deep learning models.
 https://tensorflownet.readthedocs.io</Description>
     <AssemblyVersion>0.12.0.0</AssemblyVersion>
     <PackageReleaseNotes>Changes since v0.11.0:
-</PackageReleaseNotes>
+1: Add ICanBeFlattened for nest.flatten2.
+2:</PackageReleaseNotes>
     <LangVersion>7.3</LangVersion>
     <FileVersion>0.12.0.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>

src/TensorFlowNET.Core/Tensors/Tensor.cs

@@ -39,7 +39,7 @@ namespace Tensorflow
     /// Internally, TensorFlow represents tensors as n-dimensional arrays of base datatypes.
     /// </summary>
     [SuppressMessage("ReSharper", "ConvertToAutoProperty")]
-    public partial class Tensor : DisposableObject, ITensorOrOperation, _TensorLike
+    public partial class Tensor : DisposableObject, ITensorOrOperation, _TensorLike, ITensorOrTensorArray
     {
         private readonly int _id;
         private readonly Operation _op;
@@ -178,7 +178,7 @@ namespace Tensorflow
         /// </summary>
         public void set_shape(TensorShape shape) 
         {
-            this.shape = shape.rank > 0 ? shape.dims : null;
+            this.shape = shape.rank >= 0 ? shape.dims : null;
         }
 
         /// <summary>

src/TensorFlowNET.Core/Util/nest.py.cs

@@ -223,9 +223,10 @@ namespace Tensorflow.Util
         }
 
         public static object[] flatten2(ICanBeFlattened structure)
-        {
-            return structure.Flatten();
-        }
+            => structure.Flatten();
+
+        public static T[] flatten2<T>(T[] structure)
+            => structure;
 
         private static void _flatten_recursive<T>(T obj, List<T> list)
         {
@@ -423,7 +424,7 @@ namespace Tensorflow.Util
         /// <returns> `flat_sequence` converted to have the same recursive structure as
         /// `structure`.
         /// </returns>
-        public static object pack_sequence_as(object structure, IEnumerable<object> flat_sequence)
+        public static object pack_sequence_as(object structure, IEnumerable<object> flat_sequence, bool expand_composites = false)
         {
             List<object> flat = null;
             if (flat_sequence is List<object>)