Merge master

Author: Sebastian-roko

README.md

@@ -9,7 +9,7 @@
 [![Badge](https://img.shields.io/badge/link-996.icu-red.svg)](https://996.icu/#/en_US)
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/javiercp/BinderTF.NET/master?urlpath=lab)
 
-*master branch is based on tensorflow 2.3 now, v0.15-tensorflow1.15 is from tensorflow1.15.*
+*master branch is based on tensorflow v2.4, v0.3x branch is based on tensorflow v2.3, v0.15-tensorflow1.15 is from tensorflow1.15.*
 
 
 ![tensors_flowing](docs/assets/tensors_flowing.gif)
@@ -30,7 +30,8 @@ Go through the online docs [TensorFlow for .NET](https://scisharp.github.io/tens
 
 | TensorFlow                 | tf native1.14, cuda 10.0 | tf native 1.15, cuda 10.0 | tf native 2.3, cuda 10.1 | tf native 2.4, cuda 11 |
 | -------------------------- | ------------- | -------------- | ------------- | ------------- |
-| tf.net 0.3x, tf.keras 0.2 |               |                | x | not compatible |
+| tf.net 0.4x, tf.keras 0.5 |  |  |  | x |
+| tf.net 0.3x, tf.keras 0.4 |               |                | x |  |
 | tf.net 0.2x          |               | x | x |              |
 | tf.net 0.15          | x | x |               |               |
 | tf.net 0.14          | x |                |               |               |
@@ -50,10 +51,10 @@ PM> Install-Package TensorFlow.Keras
 
 ### Install tensorflow binary
 ### For CPU version
-PM> Install-Package SciSharp.TensorFlow.Redist -Version 2.3.1
+PM> Install-Package SciSharp.TensorFlow.Redist
 
 ### For GPU version (CUDA and cuDNN are required)
-PM> Install-Package SciSharp.TensorFlow.Redist-Windows-GPU -Version 2.3.1
+PM> Install-Package SciSharp.TensorFlow.Redist-Windows-GPU
 ```
 
 Import TF.NET and Keras API in your project.

TensorFlow.NET.sln

@@ -7,7 +7,7 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Binding", "src\T
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Benchmark", "src\TensorFlowNet.Benchmarks\Tensorflow.Benchmark.csproj", "{3A6EB896-604F-4E25-B677-B8103BCF3D2E}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.UnitTest", "test\TensorFlowNET.UnitTest\Tensorflow.UnitTest.csproj", "{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}"
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Binding.UnitTest", "test\TensorFlowNET.UnitTest\Tensorflow.Binding.UnitTest.csproj", "{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}"
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Console", "src\TensorFlowNET.Console\Tensorflow.Console.csproj", "{03F06299-3F4B-4449-A709-3A647657BC0C}"
 EndProject

src/TensorFlowNET.Console/MemoryBasicTest.cs

@@ -4,6 +4,8 @@
 using Tensorflow.Keras.Engine.DataAdapters;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
+using System.Linq;
+using System.Collections.Generic;
 
 namespace Tensorflow
 {
@@ -35,13 +37,15 @@ public Action<int, int> Constant2x3
         public Action<int, int> ConstantString
             => (epoch, iterate) =>
             {
-                var tensor = tf.constant(new string[] 
+                var strList = new string[]
                 {
                     "Biden immigration bill would put millions of illegal immigrants on 8-year fast-track to citizenship",
                     "The Associated Press, which also reported that the eight-year path is in the bill.",
                     "The bill would also include provisions to stem the flow of migration by addressing root causes of migration from south of the border."
-                });
-                var data = tensor.numpy();
+                };
+
+                var tensor = tf.constant(strList, TF_DataType.TF_STRING);
+                var data = tensor.StringData();
             };
 
         public Action<int, int> Variable
@@ -108,16 +112,18 @@ public Action<int, int> Conv2DWithTensor
                 var strides = new[] { 1, 1, 1, 1 };
                 var dilations = new[] { 1, 1, 1, 1 };
 
-                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
-                    "Conv2D", null,
-                    null,
-                    input, filter,
-                    "strides", strides,
-                    "use_cudnn_on_gpu", true,
-                    "padding", "VALID",
-                    "explicit_paddings", new int[0],
-                    "data_format", "NHWC",
-                    "dilations", dilations);
+                var results = tf.Runner.TFE_FastPathExecute(new FastPathOpExecInfo("Conv2D", null, input, filter)
+                {
+                    attrs = ConvertToDict(new
+                    {
+                        strides,
+                        use_cudnn_on_gpu = true,
+                        padding = "VALID",
+                        explicit_paddings = new int[0],
+                        data_format = "NHWC",
+                        dilations
+                    })
+                });
             };
 
         public Action<int, int> Conv2DWithVariable
@@ -128,16 +134,18 @@ public Action<int, int> Conv2DWithVariable
                 var strides = new[] { 1, 1, 1, 1 };
                 var dilations = new[] { 1, 1, 1, 1 };
 
-                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
-                    "Conv2D", null,
-                    null,
-                    input, filter,
-                    "strides", strides,
-                    "use_cudnn_on_gpu", true,
-                    "padding", "VALID",
-                    "explicit_paddings", new int[0],
-                    "data_format", "NHWC",
-                    "dilations", dilations);
+                var results = tf.Runner.TFE_FastPathExecute(new FastPathOpExecInfo("Conv2D", null, input, filter)
+                {
+                    attrs = ConvertToDict(new
+                    {
+                        strides,
+                        use_cudnn_on_gpu = true,
+                        padding = "VALID",
+                        explicit_paddings = new int[0],
+                        data_format = "NHWC",
+                        dilations
+                    })
+                });
             };
 
         public Action<int, int> Dataset

src/TensorFlowNET.Console/Program.cs

@@ -47,7 +47,7 @@ static void BasicTest(MemoryMonitor mm)
             // explaination of constant
             mm.Execute(10, 100 * batchSize, basic.Constant2x3);
 
-            mm.Execute(10, 100 * batchSize, basic.ConstantString);
+            mm.Execute(10, batchSize, basic.ConstantString);
 
             // 100K float variable.
             mm.Execute(10, batchSize, basic.Variable);

src/TensorFlowNET.Console/Tensorflow.Console.csproj

@@ -2,7 +2,7 @@
 
   <PropertyGroup>
     <OutputType>Exe</OutputType>
-    <TargetFramework>netcoreapp3.1</TargetFramework>
+    <TargetFramework>net5.0</TargetFramework>
     <RootNamespace>Tensorflow</RootNamespace>
     <AssemblyName>Tensorflow</AssemblyName>
     <Platforms>AnyCPU;x64</Platforms>
@@ -11,10 +11,11 @@
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
     <DefineConstants>TRACE;DEBUG</DefineConstants>
+    <PlatformTarget>x64</PlatformTarget>
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.3.1" />
+    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.4.1" />
   </ItemGroup>
 
   <ItemGroup>

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

@@ -13,6 +13,7 @@ You may obtain a copy of the License at
    See the License for the specific language governing permissions and
    limitations under the License.
 ******************************************************************************/
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -37,8 +38,8 @@ public Tensor diag(Tensor diagonal, string name = null)
             public Tensor matmul(Tensor a, Tensor b)
                 => math_ops.matmul(a, b);
 
-            public Tensor batch_matmul(Tensor x, Tensor y)
-                => gen_math_ops.batch_mat_mul(x, y);
+            public Tensor batch_matmul(Tensor x, Tensor y, bool adj_x = false, bool adj_y = false, string name = null)
+                => math_ops.batch_matmul(x, y, adj_x: adj_x, adj_y: adj_y, name: name);
         }
 
         public Tensor diag(Tensor diagonal, string name = null)
@@ -47,7 +48,32 @@ public Tensor diag(Tensor diagonal, string name = null)
         public Tensor matmul(Tensor a, Tensor b)
             => math_ops.matmul(a, b);
 
-        public Tensor batch_matmul(Tensor x, Tensor y)
-            => gen_math_ops.batch_mat_mul(x, y);
+        /// <summary>
+        /// Multiply slices of the two matrices "x" and "y".
+        /// </summary>
+        /// <remarks>
+        /// The `BatchMatMul` operation is embedded into the
+        /// `MatMul` operation on the DLL side. However the expected
+        /// attributes are not the same, hence we need to expose this
+        /// method to have the right args list on the `_apply_op_helper`
+        /// function.
+        ///
+        /// For each rank > 2 the first rank - 2 dimensions are considered
+        /// as fixed, and have to be consistent across the two matrices. A
+        /// common matrix multiplication is then applied over the residual
+        /// 2 dimensions.
+        ///
+        /// e.g.
+        ///     x is (3, 6, 12); y is (3, 12, 6)
+        ///     batch_matmul(x, y) ==> (3, 6, 6)
+        /// </remarks>
+        /// <param name="x"></param>
+        /// <param name="y"></param>
+        /// <param name="adj_x"></param>
+        /// <param name="adj_y"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public Tensor batch_matmul(Tensor x, Tensor y, bool adj_x = false, bool adj_y = false, string name = null)
+            => math_ops.batch_matmul(x, y, adj_x: adj_x, adj_y: adj_y, name: name);
     }
 }

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

@@ -32,6 +32,28 @@ public Tensor log(Tensor x, string name = null)
             /// <returns></returns>
             public Tensor erf(Tensor x, string name = null)
                 => math_ops.erf(x, name);
+
+            /// <summary>
+            /// 
+            /// </summary>
+            /// <param name="arr"></param>
+            /// <param name="weights"></param>
+            /// <param name="minlength"></param>
+            /// <param name="maxlength"></param>
+            /// <param name="dtype"></param>
+            /// <param name="name"></param>
+            /// <param name="axis"></param>
+            /// <param name="binary_output"></param>
+            /// <returns></returns>
+            public Tensor bincount(Tensor arr, Tensor weights = null,
+                Tensor minlength = null,
+                Tensor maxlength = null,
+                TF_DataType dtype = TF_DataType.TF_INT32,
+                string name = null,
+                TensorShape axis = null,
+                bool binary_output = false)
+                => math_ops.bincount(arr, weights: weights, minlength: minlength, maxlength: maxlength,
+                    dtype: dtype, name: name, axis: axis, binary_output: binary_output);
         }
 
         public Tensor abs(Tensor x, string name = null)

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

@@ -14,17 +14,18 @@ You may obtain a copy of the License at
    limitations under the License.
 ******************************************************************************/
 
+using System;
 using Tensorflow.Framework;
 
 namespace Tensorflow
 {
     public partial class tensorflow
     {
-        public SparseTensor<T> SparseTensor<T>(long[,] indices, T[] values, long[] dense_shape)
-            => new SparseTensor<T>(indices, values, dense_shape);
+        public SparseTensor SparseTensor(long[,] indices, Array values, long[] dense_shape)
+            => new SparseTensor(indices, values, dense_shape);
 
-        public Tensor sparse_tensor_to_dense<T>(SparseTensor<T> sp_input,
-            T default_value = default,
+        public Tensor sparse_tensor_to_dense(SparseTensor sp_input,
+            Array default_value = default,
             bool validate_indices = true,
             string name = null)
             => gen_sparse_ops.sparse_to_dense(sp_input.indices,

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

@@ -14,6 +14,8 @@ You may obtain a copy of the License at
    limitations under the License.
 ******************************************************************************/
 
+using Tensorflow.Framework;
+
 namespace Tensorflow
 {
     public partial class tensorflow
@@ -24,6 +26,30 @@ public class StringsApi
         {
             string_ops ops = new string_ops();
 
+            /// <summary>
+            /// Converts all uppercase characters into their respective lowercase replacements.
+            /// </summary>
+            /// <param name="input"></param>
+            /// <param name="encoding"></param>
+            /// <param name="name"></param>
+            /// <returns></returns>
+            public Tensor lower(Tensor input, string encoding = "", string name = null)
+                => ops.lower(input: input, encoding: encoding, name: name);
+
+            /// <summary>
+            /// 
+            /// </summary>
+            /// <param name="input"></param>
+            /// <param name="pattern"></param>
+            /// <param name="rewrite"></param>
+            /// <param name="replace_global"></param>
+            /// <param name="name"></param>
+            /// <returns></returns>
+            public Tensor regex_replace(Tensor input, string pattern, string rewrite,
+                bool replace_global = true, string name = null)
+                => ops.regex_replace(input, pattern, rewrite,
+                    replace_global: replace_global, name: name);
+
             /// <summary>
             /// Return substrings from `Tensor` of strings.
             /// </summary>
@@ -40,6 +66,27 @@ public Tensor substr(Tensor input, int pos, int len,
             public Tensor substr(string input, int pos, int len,
                     string name = null, string @uint = "BYTE")
                 => ops.substr(input, pos, len, @uint: @uint, name: name);
+
+            /// <summary>
+            /// String lengths of `input`.
+            /// </summary>
+            /// <param name="input"></param>
+            /// <param name="name"></param>
+            /// <param name="unit"></param>
+            /// <returns></returns>
+            public Tensor string_length(Tensor input, string name = null, string unit = "BYTE")
+                => ops.string_length(input, name: name, unit: unit);
+
+            public RaggedTensor split(Tensor input, string sep = "", int maxsplit = -1, string name = null)
+                => ops.string_split_v2(input, sep: sep, maxsplit : maxsplit, name : name);
+
+            public (RaggedTensor, RaggedTensor) unicode_decode_with_offsets(Tensor input, string input_encoding, 
+                string errors = "replace", int replacement_char = 0xFFFD, 
+                bool replace_control_characters = false, string name = null)
+                => ops.unicode_decode_with_offsets(input, input_encoding, errors,
+                    replacement_char: replacement_char,
+                    replace_control_characters: replace_control_characters,
+                    name: name);
         }
     }
 }