WhileContext BuildLoop

Author: Oceania2018

src/TensorFlowNET.Core/APIs/tf.control_flow.cs

@@ -37,7 +37,7 @@ public Tensor cond(Tensor pred,
         public Operation group<T>(T[] inputs, string name = null) where T : ITensorOrOperation
             => control_flow_ops.group(inputs, name: name);
 
-        public Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, Tensor[] loop_vars,
+        /*public Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, Tensor[] loop_vars,
             TensorShape shape_invariants = null,
             int parallel_iterations = 10,
             bool back_prop = true,
@@ -52,7 +52,7 @@ public Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, T
                 swap_memory: swap_memory,
                 name: name,
                 maximum_iterations: maximum_iterations,
-                return_same_structure: return_same_structure);
+                return_same_structure: return_same_structure);*/
 
         public _ControlDependenciesController control_dependencies(ITensorOrOperation[] control_inputs) 
             => ops.control_dependencies(control_inputs);

src/TensorFlowNET.Core/Operations/ControlFlows/LoopVar.cs

@@ -0,0 +1,25 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Operations
+{
+    internal class LoopVar<TItem>
+    {
+        public Tensor Counter { get; }
+        public TItem[] Items { get; }
+        public TItem Item { get; }
+
+        public LoopVar(Tensor counter, TItem[] items)
+        {
+            Counter = counter;
+            Items = items;
+        }
+
+        public LoopVar(Tensor counter, TItem item)
+        {
+            Counter = counter;
+            Item = item;
+        }
+    }
+}

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

@@ -0,0 +1,32 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Operations
+{
+    internal class BodyItemInRnnWhileLoop
+    {
+        /// <summary>
+        /// int32 scalar Tensor.
+        /// </summary>
+        public Tensor time { get; set; }
+        /// <summary>
+        /// List of `TensorArray`s that represent the output.
+        /// </summary>
+        public TensorArray[] output_ta_t { get; set; }
+        /// <summary>
+        /// nested tuple of vector tensors that represent the state.
+        /// </summary>
+        public Tensor state { get; set; }
+
+        public BodyItemInRnnWhileLoop(Tensor time, TensorArray[] output_ta_t, Tensor state)
+        {
+            this.time = time;
+            this.output_ta_t = output_ta_t;
+            this.state = state;
+        }
+
+        public static implicit operator (Tensor, TensorArray[], Tensor)(BodyItemInRnnWhileLoop item)
+            => (item.time, item.output_ta_t, item.state);
+    }
+}

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

@@ -145,7 +145,7 @@ private static (Tensor, Tensor) _dynamic_rnn_loop(RNNCell cell, Tensor inputs, T
             {
                 var ta = new TensorArray(dtype: dtype_,
                                         size: time_steps,
-                                        element_shape: new[] { element_shape },
+                                        element_shape: element_shape,
                                         tensor_array_name: base_name + name);
                 return ta;
             };
@@ -178,19 +178,29 @@ private static (Tensor, Tensor) _dynamic_rnn_loop(RNNCell cell, Tensor inputs, T
 
             // Make sure that we run at least 1 step, if necessary, to ensure
             // the TensorArrays pick up the dynamic shape.
-            Tensor loop_bound;
+            Tensor loop_bound = null;
             if (in_graph_mode)
                 loop_bound = math_ops.minimum(
                     time_steps, math_ops.maximum(1, max_sequence_length));
 
-            /*Func<Tensor, Tensor> cond = (ctime) =>
+            Func<BodyItemInRnnWhileLoop, Tensor> cond = (item) =>
             {
-                return null;
+                return time < loop_bound;
             };
 
-            control_flow_ops.while_loop(
+            // Take a time step of the dynamic RNN.
+            Func<BodyItemInRnnWhileLoop, BodyItemInRnnWhileLoop> _time_step = (item) =>
+            {
+                return item;
+            };
+
+            control_flow_ops.while_loop<BodyItemInRnnWhileLoop>(
               cond: cond,
-              body = );*/
+              body: _time_step,
+              loop_vars: new BodyItemInRnnWhileLoop(time, output_ta.ToArray(), state),
+              parallel_iterations: parallel_iterations,
+              maximum_iterations: time_steps,
+              swap_memory: swap_memory);
 
             throw new NotImplementedException("");
         }

src/TensorFlowNET.Core/Operations/TensorArray.cs

@@ -39,7 +39,7 @@ public class TensorArray
 
         public TensorArray(TF_DataType dtype, Tensor size = default, bool? clear_after_read = null, bool? dynamic_size = null,
             string tensor_array_name = null, Tensor handle = null, Tensor flow = null,
-            bool infer_shape = true, TensorShape[] element_shape = null,
+            bool infer_shape = true, TensorShape element_shape = null,
             bool colocate_with_first_write_call = true, string name = null)
         {
             _implementation = new _GraphTensorArray(dtype, 

src/TensorFlowNET.Core/Operations/_GraphTensorArray.cs

@@ -44,7 +44,7 @@ internal class _GraphTensorArray
 
         public _GraphTensorArray(TF_DataType dtype, Tensor size, bool? dynamic_size = null,
             bool? clear_after_read = null, string tensor_array_name = null, Tensor handle = null, Tensor flow = null, 
-            bool infer_shape = true, TensorShape[] element_shape = null, 
+            bool infer_shape = true, TensorShape element_shape = null, 
             bool colocate_with_first_write_call = true, string name = null)
         {
             clear_after_read = clear_after_read ?? true;
@@ -68,7 +68,7 @@ public _GraphTensorArray(TF_DataType dtype, Tensor size, bool? dynamic_size = nu
             else
             {
                 _infer_shape = true;
-                _element_shape = new List<TensorShape> { };
+                _element_shape = new List<TensorShape> { element_shape };
             }
 
             tf_with(ops.name_scope(name, "TensorArray", new { handle, size, flow }), scope =>
@@ -135,7 +135,7 @@ public TensorArray scatter(Tensor indices, Tensor value, string name = null)
 
                 var ta = new TensorArray(_dtype,
                     infer_shape:_infer_shape,
-                    element_shape: _element_shape.ToArray(),
+                    element_shape: _element_shape[0],
                     dynamic_size: _dynamic_size,
                     handle: _handle,
                     flow: flow_out,

src/TensorFlowNET.Core/Operations/control_flow_ops.cs

@@ -485,7 +485,7 @@ public static Tensor[] cond<T>(Tensor pred,
             });
         }
 
-        public static Tensor[] _convert_flows_to_tensorarrays<T>(T[] tensors_or_tensorarrays, Tensor[] tensors_or_flows)
+        public static Tensor[] _convert_flows_to_tensorarrays<T>(T 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;
@@ -591,18 +591,18 @@ public static Tensor ZerosLikeOutsideLoop(Operation op, int index)
         /// <param name="body"></param>
         /// <param name="loop_vars"></param>
         /// <param name="i"></param>
-        public static Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, Tensor[] loop_vars,
+        public static Tensor while_loop<TItem>(Func<TItem, Tensor> cond, Func<TItem, TItem> body, TItem loop_vars,
             TensorShape shape_invariants = null,
             int parallel_iterations = 10,
             bool back_prop = true,
             bool swap_memory = false,
             string name = null,
-            int? maximum_iterations = null,
+            Tensor maximum_iterations = null,
             bool return_same_structure = false)
         {
             tf_with(ops.name_scope(name, "while", loop_vars), scope =>
             {
-                if (loop_vars == null || loop_vars.Length == 0)
+                if (loop_vars == null)
                     throw new ValueError("No loop variables provided");
                 if (cond == null)
                     throw new ValueError("cond must be callable.");
@@ -611,6 +611,28 @@ public static Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor>
                 if (parallel_iterations < 1)
                     throw new ValueError("parallel_iterations must be a positive integer.");
 
+                var try_to_pack = loop_vars is Tensor && !return_same_structure;
+                var counter = constant_op.constant(0, dtype: maximum_iterations.dtype, name: "iteration_counter");
+                var orig_cond = cond;
+                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;
+
+                if (try_to_pack)
+                {
+
+                }
+                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));
+                }
+                try_to_pack = false;
+
                 var loop_context = new WhileContext(
                     maximum_iterations: maximum_iterations,
                     parallel_iterations: parallel_iterations,
@@ -620,7 +642,7 @@ public static Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor>
                 if (loop_context.outer_context == null)
                     ops.add_to_collection(tf.GraphKeys.WHILE_CONTEXT, loop_context);
 
-                var results = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants,
+                var results = loop_context.BuildLoop(cond_buildloop, body_buildloop, loop_vars, shape_invariants,
                                     return_same_structure);
 
                 if (maximum_iterations != null)

src/TensorFlowNET.Core/Operations/gen_data_flow_ops.cs

@@ -28,12 +28,9 @@ public static Tensor dynamic_stitch(Tensor[] indices, Tensor[] data, string name
         }
 
         public static (Tensor, Tensor) tensor_array_v3<T>(T size, TF_DataType dtype = TF_DataType.DtInvalid, 
-            TensorShape[] element_shape = null, bool dynamic_size = false, bool clear_after_read = true, 
-            bool identical_element_shapes = false, string tensor_array_name = "tensor_array_name", string name = null)
+            TensorShape element_shape = null, bool dynamic_size = false, bool clear_after_read = true, 
+            bool identical_element_shapes = false, string tensor_array_name = "", string name = null)
         {
-            if (tensor_array_name == null)
-                tensor_array_name = string.Empty;
-
             var _op = _op_def_lib._apply_op_helper("TensorArrayV3", name, new
             {
                 size,

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

@@ -223,7 +223,6 @@ public static List<T> flatten<T>(T structure)
 
         private static void _flatten_recursive<T>(T obj, List<T> list)
         {
-
             switch(obj)
             {
                 case IDictionary dict:

src/TensorFlowNET.Core/tensorflow.cs

@@ -93,14 +93,14 @@ public Session Session()
             return new Session().as_default();
         }
 
-        public Session Session(Graph graph, SessionOptions opts = null)
+        public Session Session(Graph graph, ConfigProto config = null)
         {
-            return new Session(graph, opts: opts).as_default();
+            return new Session(graph, config: config).as_default();
         }
 
-        public Session Session(SessionOptions opts)
+        public Session Session(ConfigProto config)
         {
-            return new Session(null, opts).as_default();
+            return new Session(null, config).as_default();
         }
 
         public void __init__()