tf.zeros

docs/source/Constant.md

@@ -47,4 +47,14 @@ var tensor = tf.constant(nd);
 
 Now let's explore how constant works.
 
-现在让我探究一下`tf.constant`是怎么工作的。
+现在让我探究一下`tf.constant`是怎么工作的。
+
+
+
+##### Other functions to create a Constant
+
+* tf.zeros
+* tf.zeros_like
+* tf.ones
+* tf.ones_like
+* tf.fill

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

@@ -36,13 +36,13 @@ namespace Tensorflow
         {
             Tensor rank;
             string name;
-            using (var namescop = new ops.name_scope<Tensor>("", "Rank", new List<Tensor> { input }))
+            using (var namescop = new ops.name_scope("", "Rank", new List<Tensor> { input }))
             {
                 name = namescop;
                 rank = gen_array_ops.rank(input, namescop);
             }
 
-            using (var namescope = new ops.name_scope<Tensor>("range", "Range", new List<Tensor> { 0D, input, 1D }))
+            using (var namescope = new ops.name_scope("range", "Range", new List<Tensor> { 0D, input, 1D }))
             {
                 name = namescope;
                 var start = ops.convert_to_tensor(0D);

src/TensorFlowNET.Core/Gradients/gradients_impl.py.cs

@@ -50,7 +50,7 @@ namespace Tensorflow
             all.AddRange(grad_ys1);
 
             string grad_scope = "";
-            using (var namescope = new ops.name_scope<Tensor>(name, "gradients", values: all))
+            using (var namescope = new ops.name_scope(name, "gradients", values: all))
             {
                 grad_scope = namescope;
                 // Get a uid for this call to gradients that can be used to help

src/TensorFlowNET.Core/Operations/OpDefLibrary.cs

@@ -41,7 +41,7 @@ namespace Tensorflow
             var input_types = new List<TF_DataType>();
 
             string scope = "";
-            using (var namescope = new ops.name_scope<object>(name))
+            using (var namescope = new ops.name_scope(name))
             {
                 scope = namescope;
 

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

@@ -0,0 +1,56 @@
+using NumSharp.Core;
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public class array_ops
+    {
+        public static Tensor zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = "")
+        {
+            Tensor output = null;
+
+            dtype = dtype.as_base_dtype();
+            Python.with(new ops.name_scope(name, "zeros", shape), self =>
+            {
+                name = self as ops.name_scope;
+                switch (dtype)
+                {
+                    case TF_DataType.TF_BOOL:
+                        output = _constant_if_small(false, shape, dtype, name);
+                        break;
+                    case TF_DataType.TF_DOUBLE:
+                        output = _constant_if_small(0.0D, shape, dtype, name);
+                        break;
+                    case TF_DataType.TF_FLOAT:
+                        output = _constant_if_small(0.0F, shape, dtype, name);
+                        break;
+                    case TF_DataType.TF_INT32:
+                        output = _constant_if_small(0, shape, dtype, name);
+                        break;
+                    default:
+                        break;
+                }
+            });
+
+            return output;
+        }
+
+        private static Tensor _constant_if_small<T>(T value, Shape shape, TF_DataType dtype, string name)
+        {
+            Tensor tShape = null;
+            var nd = np.zeros<T>(shape);
+            if (shape.Size < 1000)
+            {
+                return constant_op.Constant(nd, name);
+            }
+            else
+            {
+                tShape = constant_op._tensor_shape_tensor_conversion_function(shape.as_shape(), dtype, name);
+                var c = constant_op.Constant(nd, name);
+                return gen_array_ops.fill<T>(shape, value, name);
+            }
+        }
+    }
+}

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

@@ -9,7 +9,7 @@ namespace Tensorflow
     {
         public static Operation group(List<Operation> inputs, string name = "")
         {
-            using(var namescope = new ops.name_scope<Operation>(name, "group_deps", inputs))
+            using(var namescope = new ops.name_scope(name, "group_deps", inputs))
             {
                 name = namescope;
 

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -55,5 +55,24 @@ namespace Tensorflow
 
             return _op.outputs[0];
         }
+
+        /// <summary>
+        /// Creates a tensor filled with a scalar value.
+        /// </summary>
+        /// <typeparam name="T"></typeparam>
+        /// <param name="dims"></param>
+        /// <param name="value"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public static Tensor fill<T>(int[] dims, T value, string name = "")
+        {
+            var keywords = new Dictionary<string, object>();
+            keywords.Add("dims", dims);
+            keywords.Add("value", value);
+
+            var _op = _op_def_lib._apply_op_helper("Fill", name);
+
+            return _op.outputs[0];
+        }
     }
 }

src/TensorFlowNET.Core/Python.cs

@@ -14,12 +14,12 @@ namespace Tensorflow
             Console.WriteLine(obj.ToString());
         }
 
-        public static void with(IPython py, Action action)
+        public static void with(IPython py, Action<IPython> action)
         {
             try
             {
                 py.__enter__();
-                action();
+                action(py);
             }
             catch (Exception ex)
             {

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -37,7 +37,7 @@ TensorFlow 1.13 RC.</PackageReleaseNotes>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.6.1" />
-    <PackageReference Include="NumSharp" Version="0.6.6" />
+    <PackageReference Include="NumSharp" Version="0.7.0" />
   </ItemGroup>
 
   <ItemGroup>

src/TensorFlowNET.Core/Tensors/constant_op.cs

@@ -46,5 +46,37 @@ namespace Tensorflow
 
             return op.outputs[0];
         }
+
+        /// <summary>
+        /// Function to convert TensorShape to Tensor.
+        /// </summary>
+        /// <param name="s"></param>
+        /// <param name="dtype"></param>
+        /// <param name="name"></param>
+        /// <param name="as_ref"></param>
+        /// <returns></returns>
+        public static Tensor _tensor_shape_tensor_conversion_function(TensorShape s, TF_DataType dtype = TF_DataType.DtInvalid, string name = "", bool as_ref = false)
+        {
+            var s_list = s.Dimensions;
+            var int64_value = 0;
+            foreach(var dim in s_list)
+            {
+                if (dim > Math.Pow(2, 31))
+                {
+                    int64_value = dim;
+                    break;
+                }
+            }
+
+            if(int64_value > 0)
+            {
+                dtype = TF_DataType.TF_INT32;
+            }
+
+            if (string.IsNullOrEmpty(name))
+                name = "shape_as_tensor";
+
+            return constant_op.Constant(s_list, name);
+        }
     }
 }

src/TensorFlowNET.Core/Tensors/dtypes.cs

@@ -70,5 +70,12 @@ namespace Tensorflow
                 (TF_DataType)Enum.Parse(typeof(TF_DataType), ((int)type - 100).ToString()) :
                 type;
         }
+
+        public static DataType as_base_dtype(this DataType type)
+        {
+            return (int)type > 100 ?
+                (DataType)Enum.Parse(typeof(DataType), ((int)type - 100).ToString()) :
+                type;
+        }
     }
 }

src/TensorFlowNET.Core/Tensors/tensor_util.cs

@@ -18,7 +18,7 @@ namespace Tensorflow
             var tensor_proto = new tensor_pb2.TensorProto
             {
                 Dtype = numpy_dtype.as_datatype_enum(),
-                TensorShape = shape.as_shape(nd.shape).as_proto()
+                TensorShape = shape.reshape(nd.shape).as_proto()
             };
 
             switch (nd.dtype.Name)
@@ -94,7 +94,12 @@ namespace Tensorflow
             return new TensorShape(dims.Select(x => (int)x).ToArray());
         }
 
-        public static TensorShape as_shape(this IShape shape, int[] dims)
+        public static TensorShape as_shape(this IShape shape)
+        {
+            return new TensorShape(shape.Dimensions);
+        }
+
+        public static TensorShape reshape(this IShape shape, int[] dims)
         {
             return new TensorShape(dims);
         }

src/TensorFlowNET.Core/APIs/tf.constant.cs → src/TensorFlowNET.Core/Tensors/tf.constant.cs

@@ -11,5 +11,10 @@ namespace Tensorflow
         {
             return constant_op.Constant(nd, name, verify_shape);
         }
+
+        public static Tensor zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = "")
+        {
+            return array_ops.zeros(shape, dtype, name);
+        }
     }
 }

src/TensorFlowNET.Core/Variables/RefVariable.cs

@@ -65,7 +65,7 @@ namespace Tensorflow
 
             ops.init_scope();
             var values = init_from_fn ? new List<object>() : new List<object> { initial_value };
-            using (var namescope = new ops.name_scope<object>(name, "Variable", values))
+            using (var namescope = new ops.name_scope(name, "Variable", values))
             {
                 name = namescope;
 

src/TensorFlowNET.Core/ops.name_scope.cs

@@ -7,7 +7,7 @@ namespace Tensorflow
 {
     public partial class ops
     {
-        public class name_scope<T> : IDisposable
+        public class name_scope : IPython
         {
             public string _name;
             public string _default_name;
@@ -16,7 +16,7 @@ namespace Tensorflow
             public string _name_scope;
             private object _g_manager;
 
-            public name_scope(string name, string default_name = "", List<T> values = null)
+            public name_scope(string name, string default_name = "", object values = null)
             {
                 _name = name;
                 _default_name = default_name;
@@ -24,7 +24,7 @@ namespace Tensorflow
                 // _ctx = new Context();
             }
 
-            public string __enter__()
+            public void __enter__()
             {
                 if (String.IsNullOrEmpty(_name))
                 {
@@ -39,8 +39,6 @@ namespace Tensorflow
                     g = get_default_graph();
 
                 _name_scope = g.name_scope(_name);
-
-                return _name_scope;
             }
 
             public void Dispose()
@@ -51,16 +49,17 @@ namespace Tensorflow
                 g.old_stack = "";
             }
 
+            public void __exit__()
+            {
+            }
+
             /// <summary>
             /// __enter__()
             /// </summary>
             /// <param name="ns"></param>
-            public static implicit operator string(name_scope<T> ns)
+            public static implicit operator string(name_scope ns)
             {
-                if (string.IsNullOrEmpty(ns._name_scope))
-                    return ns.__enter__();
-                else
-                    return ns._name_scope;
+                return ns._name_scope;
             }
         }
     }

test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj

@@ -6,7 +6,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="NumSharp" Version="0.6.6" />
+    <PackageReference Include="NumSharp" Version="0.7.0" />
     <PackageReference Include="TensorFlow.NET" Version="0.1.0" />
   </ItemGroup>
 

test/TensorFlowNET.UnitTest/ConstantTest.cs

@@ -2,6 +2,7 @@
 using NumSharp.Core;
 using System;
 using System.Collections.Generic;
+using System.Linq;
 using System.Text;
 using Tensorflow;
 
@@ -26,6 +27,17 @@ namespace TensorFlowNET.UnitTest
             tensor = tf.constant("Elephant");
         }
 
+        [TestMethod]
+        public void ZerosConst()
+        {
+            tensor = tf.zeros(new Shape(3, 2), TF_DataType.TF_INT32, "x");
+            Assert.AreEqual(tensor.shape[0], 3);
+            Assert.AreEqual(tensor.shape[0], 2);
+            Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 0, 0, 0, 0 }, tensor.Data<int>()));
+
+            tensor = tf.zeros(new Shape(200, 300), TF_DataType.TF_INT32, "x");
+        }
+
         [TestMethod]
         public void NDimConst()
         {

test/TensorFlowNET.UnitTest/TensorFlowNET.UnitTest.csproj

@@ -19,7 +19,7 @@
     <PackageReference Include="Microsoft.NET.Test.Sdk" Version="15.9.0" />
     <PackageReference Include="MSTest.TestAdapter" Version="1.4.0" />
     <PackageReference Include="MSTest.TestFramework" Version="1.4.0" />
-    <PackageReference Include="NumSharp" Version="0.6.6" />
+    <PackageReference Include="NumSharp" Version="0.7.0" />
     <PackageReference Include="TensorFlow.NET" Version="0.1.0" />
   </ItemGroup>