Remove internal_convert_to_tensor.

Oceania2018 · Oceania2018 · commit cfc9eb302595 · 2021-01-02T12:32:06.000-06:00
diff --git a/src/TensorFlowNET.Core/APIs/tf.tensor.cs b/src/TensorFlowNET.Core/APIs/tf.tensor.cs
@@ -19,7 +19,7 @@ namespace Tensorflow
     public partial class tensorflow
     {
         public Tensor convert_to_tensor(object value, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, TF_DataType preferred_dtype = TF_DataType.DtInvalid)
-            => ops.convert_to_tensor(value, dtype, name, preferred_dtype);
+            => ops.convert_to_tensor(value, dtype, name, preferred_dtype: preferred_dtype);
 
         public Tensor strided_slice(Tensor input, Tensor begin, Tensor end, Tensor strides = null,
             int begin_mask = 0,
diff --git a/src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs b/src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs
@@ -69,7 +69,7 @@ public Tensor AsPlaceholder(string name = null)
             return placeholder;
         }
 
-        public Tensor AsContatnt(string name = null)
+        public Tensor AsConstant(string name = null)
         {
             Tensor constant = null;
             tf_with(ops.control_dependencies(null), delegate
diff --git a/src/TensorFlowNET.Core/Framework/sparse_tensor.py.cs b/src/TensorFlowNET.Core/Framework/sparse_tensor.py.cs
@@ -29,7 +29,7 @@ public SparseTensor(long[,] indices_, T[] values_, long[] dense_shape_)
             {
                 indices = ops.convert_to_tensor(
                     indices_, name: "indices", dtype: dtypes.int64);
-                values = ops.internal_convert_to_tensor(values_, name: "values");
+                values = ops.convert_to_tensor(values_, name: "values");
                 dense_shape = ops.convert_to_tensor(
                     dense_shape_, name: "dense_shape", dtype: dtypes.int64);
             });
diff --git a/src/TensorFlowNET.Core/Graphs/FuncGraph.cs b/src/TensorFlowNET.Core/Graphs/FuncGraph.cs
@@ -13,9 +13,6 @@ namespace Tensorflow.Graphs
     /// </summary>
     public class FuncGraph : Graph
     {
-        Graph outer_graph;
-        public Graph OuterGraph => outer_graph;
-
         // _handle == IntPtr.Zero ? string.Empty : c_api.StringPiece(c_api.TF_FunctionName(_handle));
         IntPtr func_handle;
         public string FuncName => _graph_key;
@@ -42,16 +39,21 @@ public Tensor[] internal_captures()
         public FuncGraph(string name) : base()
         {
             outer_graph = ops.get_default_graph();
+            while (outer_graph.building_function)
+                outer_graph = outer_graph.OuterGraph;
             _graph_key = name;
-
+            building_function = true;
             tf.Context.graph_mode();
             as_default();
         }
 
         public FuncGraph(IntPtr handle, string name, Dictionary<string, string> attrs) : base()
         {
             outer_graph = ops.get_default_graph();
+            while (outer_graph.building_function)
+                outer_graph = outer_graph.OuterGraph;
             _graph_key = name;
+            building_function = true;
             Attrs = attrs;
             // Will to test if FuncGraph has memory leak
             // c_api.TF_DeleteGraph(_handle);
@@ -108,7 +110,7 @@ public override Operation create_op(string op_type, Tensor[] inputs, TF_DataType
             return base.create_op(op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device);
         }
 
-        Tensor capture(Tensor tensor, string name = null, TF_DataType shape = TF_DataType.DtInvalid)
+        public Tensor capture(Tensor tensor, string name = null, TF_DataType shape = TF_DataType.DtInvalid)
         {
             if(tensor is EagerTensor)
             {
diff --git a/src/TensorFlowNET.Core/Graphs/Graph.cs b/src/TensorFlowNET.Core/Graphs/Graph.cs
@@ -118,6 +118,9 @@ public int seed
             }
         }
 
+        protected Graph outer_graph;
+        public Graph OuterGraph => outer_graph;
+
         public Graph()
         {
             _handle = c_api.TF_NewGraph();
diff --git a/src/TensorFlowNET.Core/Operations/OpDefLibrary.cs b/src/TensorFlowNET.Core/Operations/OpDefLibrary.cs
@@ -148,7 +148,7 @@ public Operation _apply_op_helper(string op_type_name, string name = null, Dicti
                         else if (default_type_attr_map.ContainsKey(input_arg.TypeAttr))
                             default_dtype = (DataType)default_type_attr_map[input_arg.TypeAttr];
 
-                        var value = ops.internal_convert_to_tensor(values,
+                        var value = ops.convert_to_tensor(values,
                             name: input_name,
                             dtype: dtype.as_tf_dtype(),
                             as_ref: input_arg.IsRef,
diff --git a/src/TensorFlowNET.Core/Training/Saving/saveable_object_util.py.cs b/src/TensorFlowNET.Core/Training/Saving/saveable_object_util.py.cs
@@ -66,7 +66,7 @@ public static IEnumerable<MySaveableObject> saveable_objects_for_op(Tensor op, s
             else
             {
                 ops.init_scope();
-                var variable = ops.internal_convert_to_tensor(op, as_ref: true);
+                var variable = ops.convert_to_tensor(op, as_ref: true);
                 if (variable.dtype.is_ref_dtype())
                     yield return new ReferenceVariableSaveable(variable, "", name);
                 else
@@ -103,7 +103,7 @@ public static Dictionary<string, Tensor> op_list_to_dict(IVariableV1[] op_list,
                             if (!var.dtype.is_ref_dtype())
                                 tensor = var.GraphElement;
                             else
-                                tensor = ops.internal_convert_to_tensor(var, as_ref: true);
+                                tensor = ops.convert_to_tensor(var, as_ref: true);
                         }
 
                         if (tensor.op.type == "ReadVariableOp")
diff --git a/src/TensorFlowNET.Core/ops.cs b/src/TensorFlowNET.Core/ops.cs
@@ -24,6 +24,7 @@ limitations under the License.
 using System.Threading;
 using Tensorflow.Contexts;
 using Tensorflow.Eager;
+using Tensorflow.Graphs;
 using Tensorflow.Util;
 using static Tensorflow.Binding;
 
@@ -101,14 +102,44 @@ public static Graph _get_graph_from_inputs(Tensors op_input_list, Graph graph =
         public static Tensor convert_to_tensor(object value,
             TF_DataType dtype = TF_DataType.DtInvalid,
             string name = null,
+            bool as_ref = false,
             TF_DataType preferred_dtype = TF_DataType.DtInvalid,
             Context ctx = null)
         {
-            return internal_convert_to_tensor(value,
-                dtype: dtype,
-                name: name,
-                preferred_dtype: preferred_dtype,
-                as_ref: false);
+            if (dtype == TF_DataType.DtInvalid)
+                dtype = preferred_dtype;
+
+            if (value is EagerTensor eager_tensor)
+            {
+                if (tf.executing_eagerly())
+                    return eager_tensor;
+                /*else
+                {
+                    var graph = get_default_graph();
+                    if (!graph.building_function)
+                        throw new RuntimeError("Attempting to capture an EagerTensor without building a function.");
+                    return (graph as FuncGraph).capture(eager_tensor, name: name);
+                }*/
+            }
+
+            Tensor ret = value switch
+            {
+                NDArray nd => constant_op.constant(nd, dtype: dtype, name: name),
+                EagerTensor tensor => tensor.dtype == TF_DataType.TF_RESOURCE
+                            ? tensor.AsPlaceholder(name: name)
+                            : tensor.AsConstant(name: name),
+                Tensor tensor => tensor,
+                Tensor[] tensors => array_ops._autopacking_helper(tensors, dtype, name == null ? "packed" : name),
+                RefVariable varVal => varVal._TensorConversionFunction(dtype: dtype, name: name, as_ref: as_ref),
+                ResourceVariable varVal => varVal._TensorConversionFunction(dtype: dtype, name: name, as_ref: as_ref),
+                TensorShape ts => constant_op.constant(ts.dims, dtype: dtype, name: name),
+                int[] dims => constant_op.constant(dims, dtype: dtype, name: name),
+                string str => constant_op.constant(str, dtype: tf.@string, name: name),
+                object[] objects => array_ops._autopacking_conversion_function(objects, dtype: dtype, name: name),
+                _ => constant_op.constant(value, dtype: dtype, name: name)
+            };
+
+            return ret;
         }
 
 
@@ -118,9 +149,7 @@ public static Tensor convert_to_tensor_or_composite(Tensor value, TF_DataType dt
         }
 
         public static Tensor internal_convert_to_tensor_or_composite(Tensor value, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool as_ref = false)
-        {
-            return internal_convert_to_tensor(value, dtype: dtype, name: name, as_ref: as_ref);
-        }
+            => convert_to_tensor(value, dtype: dtype, name: name, as_ref: as_ref);
 
         /// <summary>
         /// Wrapper for `Graph.control_dependencies()` using the default graph.
@@ -460,52 +489,12 @@ public static Tensor[] internal_convert_n_to_tensor(object values, TF_DataType d
             foreach ((int i, object value) in enumerate(values as object[]))
             {
                 string n = string.IsNullOrEmpty(name) ? "" : $"{name}_{i}";
-                ret.Add(internal_convert_to_tensor(value, dtype: dtype, name: n, as_ref: as_ref, preferred_dtype: preferred_dtype));
+                ret.Add(convert_to_tensor(value, dtype: dtype, name: n, as_ref: as_ref, preferred_dtype: preferred_dtype));
             }
 
             return ret.ToArray();
         }
 
-        public static Tensor internal_convert_to_tensor(object value, TF_DataType dtype = TF_DataType.DtInvalid,
-            string name = null, TF_DataType preferred_dtype = TF_DataType.DtInvalid,
-            bool as_ref = false,
-            string scope = null)
-        {
-            if (dtype == TF_DataType.DtInvalid)
-                dtype = preferred_dtype;
-
-            switch (value)
-            {
-                case NDArray nd:
-                    return constant_op.constant(nd, dtype: dtype, name: name);
-                case EagerTensor tensor:
-                    if (tf.executing_eagerly())
-                        return tensor;
-                    else
-                        return tensor.dtype == TF_DataType.TF_RESOURCE
-                            ? tensor.AsPlaceholder(name: name)
-                            : tensor.AsContatnt(name: name);
-                case Tensor tensor:
-                    return tensor;
-                case Tensor[] tensors:
-                    return array_ops._autopacking_helper(tensors, dtype, name == null ? "packed" : name);
-                case RefVariable varVal:
-                    return varVal._TensorConversionFunction(dtype: dtype, name: name, as_ref: as_ref);
-                case ResourceVariable varVal:
-                    return varVal._TensorConversionFunction(dtype: dtype, name: name, as_ref: as_ref);
-                case TensorShape ts:
-                    return constant_op.constant(ts.dims, dtype: dtype, name: name);
-                case string str:
-                    return constant_op.constant(value, dtype: tf.@string, name: name);
-                case int[] dims:
-                    return constant_op.constant(dims, dtype: dtype, name: name);
-                case object[] objects:
-                    return array_ops._autopacking_conversion_function(objects, dtype: dtype, name: name);
-                default:
-                    return constant_op.constant(value, dtype: dtype, name: name);
-            }
-        }
-
         public static string strip_name_scope(string name, string export_scope = "")
         {
             if (!string.IsNullOrEmpty(export_scope))
diff --git a/src/TensorFlowNET.Keras/BackendImpl.cs b/src/TensorFlowNET.Keras/BackendImpl.cs
@@ -17,6 +17,7 @@ limitations under the License.
 using NumSharp;
 using System;
 using System.Collections.Generic;
+using Tensorflow.Graphs;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.Keras
@@ -78,6 +79,12 @@ public Tensor placeholder(TensorShape shape = null,
 
         public Graph get_graph()
         {
+            if (tf.Context.executing_eagerly())
+            {
+                if (_GRAPH == null)
+                    _GRAPH = new FuncGraph("keras_graph");
+                return _GRAPH;
+            }
             return ops.get_default_graph();
         }
 
diff --git a/src/TensorFlowNET.Keras/Engine/Layer.FunctionalConstructionCall.cs b/src/TensorFlowNET.Keras/Engine/Layer.FunctionalConstructionCall.cs
@@ -1,6 +1,7 @@
 ﻿using System;
 using Tensorflow.Keras.Utils;
 using static Tensorflow.Binding;
+using static Tensorflow.KerasApi;
 
 namespace Tensorflow.Keras.Engine
 {
@@ -22,7 +23,7 @@ Tensors FunctionalConstructionCall(Tensors inputs)
             Tensors outputs = null;
             using var ctxManager = CallContext.enter();
 
-            // using var graph = tf.keras.backend.get_graph().as_default();
+            // using var graph = keras.backend.get_graph();
 
             if (!inputs.IsEagerTensor)
                 tf.Context.graph_mode(isFunc: true);

Original file line number	Diff line number	Diff line change
`@@ -19,7 +19,7 @@ namespace Tensorflow`
`19`	`19`	`public partial class tensorflow`
`20`	`20`	`{`
`21`	`21`	`public Tensor convert_to_tensor(object value, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, TF_DataType preferred_dtype = TF_DataType.DtInvalid)`
`22`		`- => ops.convert_to_tensor(value, dtype, name, preferred_dtype);`
	`22`	`+ => ops.convert_to_tensor(value, dtype, name, preferred_dtype: preferred_dtype);`
`23`	`23`
`24`	`24`	`public Tensor strided_slice(Tensor input, Tensor begin, Tensor end, Tensor strides = null,`
`25`	`25`	`int begin_mask = 0,`
Original file line number	Diff line number	Diff line change
`@@ -69,7 +69,7 @@ public Tensor AsPlaceholder(string name = null)`
`69`	`69`	`return placeholder;`
`70`	`70`	`}`
`71`	`71`
`72`		`- public Tensor AsContatnt(string name = null)`
	`72`	`+ public Tensor AsConstant(string name = null)`
`73`	`73`	`{`
`74`	`74`	`Tensor constant = null;`
`75`	`75`	`tf_with(ops.control_dependencies(null), delegate`
Original file line number	Diff line number	Diff line change
`@@ -29,7 +29,7 @@ public SparseTensor(long[,] indices_, T[] values_, long[] dense_shape_)`
`29`	`29`	`{`
`30`	`30`	`indices = ops.convert_to_tensor(`
`31`	`31`	`indices_, name: "indices", dtype: dtypes.int64);`
`32`		`- values = ops.internal_convert_to_tensor(values_, name: "values");`
	`32`	`+ values = ops.convert_to_tensor(values_, name: "values");`
`33`	`33`	`dense_shape = ops.convert_to_tensor(`
`34`	`34`	`dense_shape_, name: "dense_shape", dtype: dtypes.int64);`
`35`	`35`	`});`
Original file line number	Diff line number	Diff line change
`@@ -13,9 +13,6 @@ namespace Tensorflow.Graphs`
`13`	`13`	`/// </summary>`
`14`	`14`	`public class FuncGraph : Graph`
`15`	`15`	`{`
`16`		`- Graph outer_graph;`
`17`		`- public Graph OuterGraph => outer_graph;`
`18`		`-`
`19`	`16`	`// _handle == IntPtr.Zero ? string.Empty : c_api.StringPiece(c_api.TF_FunctionName(_handle));`
`20`	`17`	`IntPtr func_handle;`
`21`	`18`	`public string FuncName => _graph_key;`
`@@ -42,16 +39,21 @@ public Tensor[] internal_captures()`
`42`	`39`	`public FuncGraph(string name) : base()`
`43`	`40`	`{`
`44`	`41`	`outer_graph = ops.get_default_graph();`
	`42`	`+ while (outer_graph.building_function)`
	`43`	`+ outer_graph = outer_graph.OuterGraph;`
`45`	`44`	`_graph_key = name;`
`46`		`-`
	`45`	`+ building_function = true;`
`47`	`46`	`tf.Context.graph_mode();`
`48`	`47`	`as_default();`
`49`	`48`	`}`
`50`	`49`
`51`	`50`	`public FuncGraph(IntPtr handle, string name, Dictionary<string, string> attrs) : base()`
`52`	`51`	`{`
`53`	`52`	`outer_graph = ops.get_default_graph();`
	`53`	`+ while (outer_graph.building_function)`
	`54`	`+ outer_graph = outer_graph.OuterGraph;`
`54`	`55`	`_graph_key = name;`
	`56`	`+ building_function = true;`
`55`	`57`	`Attrs = attrs;`
`56`	`58`	`// Will to test if FuncGraph has memory leak`
`57`	`59`	`// c_api.TF_DeleteGraph(_handle);`
`@@ -108,7 +110,7 @@ public override Operation create_op(string op_type, Tensor[] inputs, TF_DataType`
`108`	`110`	`return base.create_op(op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device);`
`109`	`111`	`}`
`110`	`112`
`111`		`- Tensor capture(Tensor tensor, string name = null, TF_DataType shape = TF_DataType.DtInvalid)`
	`113`	`+ public Tensor capture(Tensor tensor, string name = null, TF_DataType shape = TF_DataType.DtInvalid)`
`112`	`114`	`{`
`113`	`115`	`if(tensor is EagerTensor)`
`114`	`116`	`{`
Original file line number	Diff line number	Diff line change
`@@ -118,6 +118,9 @@ public int seed`
`118`	`118`	`}`
`119`	`119`	`}`
`120`	`120`
	`121`	`+ protected Graph outer_graph;`
	`122`	`+ public Graph OuterGraph => outer_graph;`
	`123`	`+`
`121`	`124`	`public Graph()`
`122`	`125`	`{`
`123`	`126`	`_handle = c_api.TF_NewGraph();`