Release v0.60.2, change to .net standard 2.0.

Oceania2018 · Oceania2018 · commit e10e2807afa9 · 2021-08-21T08:29:17.000-05:00
diff --git a/src/TensorFlowNET.Core/NumPy/AutoNumPyAttribute.cs b/src/TensorFlowNET.Core/NumPy/AutoNumPyAttribute.cs
@@ -2,9 +2,6 @@
 using System;
 using System.Collections.Generic;
 using System.Diagnostics;
-using System.Linq;
-using Tensorflow.Eager;
-using Tensorflow.Functions;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.NumPy
diff --git a/src/TensorFlowNET.Core/Operations/array_ops.cs b/src/TensorFlowNET.Core/Operations/array_ops.cs
@@ -798,7 +798,7 @@ public static Tensor[] meshgrid<T>(T[] array, bool copy = true, bool sparse = fa
                 var output = new List<Tensor>();
                 foreach (var (i, x) in enumerate(array))
                 {
-                    var shape = s0[..i].concat(new[] { -1 }).concat(s0[(i + 1)..]);
+                    var shape = s0.Take(i).ToArray().concat(new[] { -1 }).concat(s0.Skip(i + 1).ToArray());
                     output.add(reshape(stack(x), shape));
                 }
 
diff --git a/src/TensorFlowNET.Core/Operations/linalg_ops.cs b/src/TensorFlowNET.Core/Operations/linalg_ops.cs
@@ -1,4 +1,5 @@
 ﻿using System;
+using System.Linq;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -53,7 +54,7 @@ public Tensor matrix_solve_ls(Tensor matrix, Tensor rhs,
 
         Tensor _composite_impl(Tensor matrix, Tensor rhs, Tensor l2_regularizer = null)
         {
-            Shape matrix_shape = matrix.shape[^2..];
+            Shape matrix_shape = matrix.shape.dims.Skip(matrix.shape.ndim - 2).ToArray();
             if (matrix_shape.IsFullyDefined)
             {
                 if (matrix_shape[-2] >= matrix_shape[-1])
@@ -88,7 +89,7 @@ Tensor _RegularizedGramianCholesky(Tensor matrix, Tensor l2_regularizer, bool fi
                 var small_dim = first_kind ? matrix_shape[-1] : matrix_shape[-2];
                 var identity = eye(small_dim.numpy(), batch_shape: batch_shape.shape, dtype: matrix.dtype);
                 var small_dim_static = matrix.shape[first_kind ? -1 : -2];
-                identity.shape = matrix.shape[..^2].concat(new[] { small_dim_static, small_dim_static });
+                identity.shape = matrix.shape.dims.Take(matrix.shape.ndim - 2).ToArray().concat(new[] { small_dim_static, small_dim_static });
                 gramian += l2_regularizer * identity;
             }
 
diff --git a/src/TensorFlowNET.Core/Tensorflow.Binding.csproj b/src/TensorFlowNET.Core/Tensorflow.Binding.csproj
@@ -1,11 +1,11 @@
 ﻿<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netstandard2.1</TargetFramework>
+    <TargetFramework>netstandard2.0</TargetFramework>
     <AssemblyName>TensorFlow.NET</AssemblyName>
     <RootNamespace>Tensorflow</RootNamespace>
     <TargetTensorFlow>2.2.0</TargetTensorFlow>
-    <Version>0.60.1</Version>
+    <Version>0.60.2</Version>
     <LangVersion>9.0</LangVersion>
     <Nullable>enable</Nullable>
     <Authors>Haiping Chen, Meinrad Recheis, Eli Belash</Authors>
@@ -20,7 +20,7 @@
     <Description>Google's TensorFlow full binding in .NET Standard.
 Building, training and infering deep learning models.
 https://tensorflownet.readthedocs.io</Description>
-    <AssemblyVersion>0.60.1.0</AssemblyVersion>
+    <AssemblyVersion>0.60.2.0</AssemblyVersion>
     <PackageReleaseNotes>tf.net 0.60.x and above are based on tensorflow native 2.6.0
 
 * Eager Mode is added finally.
@@ -35,7 +35,7 @@ Keras API is a separate package released as TensorFlow.Keras.
 tf.net 0.4x.x aligns with TensorFlow v2.4.1 native library.
 tf.net 0.5x.x aligns with TensorFlow v2.5.x native library.
 tf.net 0.6x.x aligns with TensorFlow v2.6.x native library.</PackageReleaseNotes>
-    <FileVersion>0.60.1.0</FileVersion>
+    <FileVersion>0.60.2.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
     <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
     <SignAssembly>true</SignAssembly>
@@ -90,8 +90,8 @@ tf.net 0.6x.x aligns with TensorFlow v2.6.x native library.</PackageReleaseNotes
 
   <ItemGroup>
     <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.139" />
-    <PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="5.0.1" />
+    <PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="5.0.2" />
     <PackageReference Include="Protobuf.Text" Version="0.5.0" />
-    <PackageReference Include="Serilog.Sinks.Console" Version="3.1.1" />
+    <PackageReference Include="Serilog.Sinks.Console" Version="4.0.0" />
   </ItemGroup>
 </Project>
diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs
@@ -62,7 +62,7 @@ public void evaluate(NDArray x, NDArray y,
             }
         }
 
-        public void evaluate(IDatasetV2 x)
+        public KeyValuePair<string, float>[] evaluate(IDatasetV2 x)
         {
             data_handler = new DataHandler(new DataHandlerArgs
             {
@@ -72,19 +72,21 @@ public void evaluate(IDatasetV2 x)
             });
 
             Binding.tf_output_redirect.WriteLine($"Testing...");
+            IEnumerable<(string, Tensor)> logs = null;
             foreach (var (epoch, iterator) in data_handler.enumerate_epochs())
             {
                 reset_metrics();
                 // callbacks.on_epoch_begin(epoch)
                 // data_handler.catch_stop_iteration();
-                IEnumerable<(string, Tensor)> results = null;
+                
                 foreach (var step in data_handler.steps())
                 {
                     // callbacks.on_train_batch_begin(step)
-                    results = test_function(iterator);
+                    logs = test_function(iterator);
                 }
-                Binding.tf_output_redirect.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", results.Select(x => $"{x.Item1}: {(float)x.Item2}")));
+                Binding.tf_output_redirect.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", logs.Select(x => $"{x.Item1}: {(float)x.Item2}")));
             }
+            return logs.Select(x => new KeyValuePair<string, float>(x.Item1, (float)x.Item2)).ToArray();
         }
 
         IEnumerable<(string, Tensor)> test_function(OwnedIterator iterator)
diff --git a/src/TensorFlowNET.Keras/Layers/StackedRNNCells.cs b/src/TensorFlowNET.Keras/Layers/StackedRNNCells.cs
@@ -51,7 +51,8 @@ public object output_size
                 }
                 else if (RNN._is_multiple_state(lastCell.state_size))
                 {
-                    return ((dynamic)Cells[-1].state_size)[0];
+                    // return ((dynamic)Cells[-1].state_size)[0];
+                    throw new NotImplementedException("");
                 }
                 else
                 {
diff --git a/src/TensorFlowNET.Keras/Tensorflow.Keras.csproj b/src/TensorFlowNET.Keras/Tensorflow.Keras.csproj
@@ -1,13 +1,13 @@
 ﻿<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netstandard2.1</TargetFramework>
+    <TargetFramework>netstandard2.0</TargetFramework>
     <AssemblyName>Tensorflow.Keras</AssemblyName>
     <LangVersion>9.0</LangVersion>
     <Nullable>enable</Nullable>
     <RootNamespace>Tensorflow.Keras</RootNamespace>
     <Platforms>AnyCPU;x64</Platforms>
-    <Version>0.6.1</Version>
+    <Version>0.6.2</Version>
     <Authors>Haiping Chen</Authors>
     <Product>Keras for .NET</Product>
     <Copyright>Apache 2.0, Haiping Chen 2021</Copyright>
@@ -37,8 +37,8 @@ Keras is an API designed for human beings, not machines. Keras follows best prac
     <RepositoryType>Git</RepositoryType>
     <SignAssembly>true</SignAssembly>
     <AssemblyOriginatorKeyFile>Open.snk</AssemblyOriginatorKeyFile>
-    <AssemblyVersion>0.6.1.0</AssemblyVersion>
-    <FileVersion>0.6.1.0</FileVersion>
+    <AssemblyVersion>0.6.2.0</AssemblyVersion>
+    <FileVersion>0.6.2.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
   </PropertyGroup>
 
diff --git a/src/TensorFlowNET.Recommenders/Tensorflow.Recommenders.csproj b/src/TensorFlowNET.Recommenders/Tensorflow.Recommenders.csproj
@@ -1,7 +1,7 @@
-<Project Sdk="Microsoft.NET.Sdk">
+﻿<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netstandard2.1</TargetFramework>
+    <TargetFramework>netstandard2.0</TargetFramework>
     <Version>0.0.1</Version>
     <Description>TensorFlow Recommenders is a library for building recommender system models using TensorFlow.</Description>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
diff --git a/src/TensorFlowNET.Text/Tensorflow.Text.csproj b/src/TensorFlowNET.Text/Tensorflow.Text.csproj
@@ -1,7 +1,7 @@
-<Project Sdk="Microsoft.NET.Sdk">
+﻿<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netstandard2.1</TargetFramework>
+    <TargetFramework>netstandard2.0</TargetFramework>
     <RootNamespace>Tensorflow.Text</RootNamespace>
     <AssemblyName>Tensorflow.Text</AssemblyName>
     <GeneratePackageOnBuild>true</GeneratePackageOnBuild>

Original file line number	Diff line number	Diff line change
`@@ -798,7 +798,7 @@ public static Tensor[] meshgrid<T>(T[] array, bool copy = true, bool sparse = fa`
`798`	`798`	`var output = new List<Tensor>();`
`799`	`799`	`foreach (var (i, x) in enumerate(array))`
`800`	`800`	`{`
`801`		`- var shape = s0[..i].concat(new[] { -1 }).concat(s0[(i + 1)..]);`
	`801`	`+ var shape = s0.Take(i).ToArray().concat(new[] { -1 }).concat(s0.Skip(i + 1).ToArray());`
`802`	`802`	`output.add(reshape(stack(x), shape));`
`803`	`803`	`}`
`804`	`804`
Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,5 @@`
`1`	`1`	`using System;`
	`2`	`+using System.Linq;`
`2`	`3`	`using static Tensorflow.Binding;`
`3`	`4`
`4`	`5`	`namespace Tensorflow`
`@@ -53,7 +54,7 @@ public Tensor matrix_solve_ls(Tensor matrix, Tensor rhs,`
`53`	`54`
`54`	`55`	`Tensor _composite_impl(Tensor matrix, Tensor rhs, Tensor l2_regularizer = null)`
`55`	`56`	`{`
`56`		`- Shape matrix_shape = matrix.shape[^2..];`
	`57`	`+ Shape matrix_shape = matrix.shape.dims.Skip(matrix.shape.ndim - 2).ToArray();`
`57`	`58`	`if (matrix_shape.IsFullyDefined)`
`58`	`59`	`{`
`59`	`60`	`if (matrix_shape[-2] >= matrix_shape[-1])`
`@@ -88,7 +89,7 @@ Tensor _RegularizedGramianCholesky(Tensor matrix, Tensor l2_regularizer, bool fi`
`88`	`89`	`var small_dim = first_kind ? matrix_shape[-1] : matrix_shape[-2];`
`89`	`90`	`var identity = eye(small_dim.numpy(), batch_shape: batch_shape.shape, dtype: matrix.dtype);`
`90`	`91`	`var small_dim_static = matrix.shape[first_kind ? -1 : -2];`
`91`		`- identity.shape = matrix.shape[..^2].concat(new[] { small_dim_static, small_dim_static });`
	`92`	`+ identity.shape = matrix.shape.dims.Take(matrix.shape.ndim - 2).ToArray().concat(new[] { small_dim_static, small_dim_static });`
`92`	`93`	`gramian += l2_regularizer * identity;`
`93`	`94`	`}`
`94`	`95`
Original file line number	Diff line number	Diff line change
`@@ -62,7 +62,7 @@ public void evaluate(NDArray x, NDArray y,`
`62`	`62`	`}`
`63`	`63`	`}`
`64`	`64`
`65`		`- public void evaluate(IDatasetV2 x)`
	`65`	`+ public KeyValuePair<string, float>[] evaluate(IDatasetV2 x)`
`66`	`66`	`{`
`67`	`67`	`data_handler = new DataHandler(new DataHandlerArgs`
`68`	`68`	`{`
`@@ -72,19 +72,21 @@ public void evaluate(IDatasetV2 x)`
`72`	`72`	`});`
`73`	`73`
`74`	`74`	`Binding.tf_output_redirect.WriteLine($"Testing...");`
	`75`	`+ IEnumerable<(string, Tensor)> logs = null;`
`75`	`76`	`foreach (var (epoch, iterator) in data_handler.enumerate_epochs())`
`76`	`77`	`{`
`77`	`78`	`reset_metrics();`
`78`	`79`	`// callbacks.on_epoch_begin(epoch)`
`79`	`80`	`// data_handler.catch_stop_iteration();`
`80`		`- IEnumerable<(string, Tensor)> results = null;`
	`81`	`+`
`81`	`82`	`foreach (var step in data_handler.steps())`
`82`	`83`	`{`
`83`	`84`	`// callbacks.on_train_batch_begin(step)`
`84`		`- results = test_function(iterator);`
	`85`	`+ logs = test_function(iterator);`
`85`	`86`	`}`
`86`		`- Binding.tf_output_redirect.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", results.Select(x => $"{x.Item1}: {(float)x.Item2}")));`
	`87`	`+ Binding.tf_output_redirect.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", logs.Select(x => $"{x.Item1}: {(float)x.Item2}")));`
`87`	`88`	`}`
	`89`	`+ return logs.Select(x => new KeyValuePair<string, float>(x.Item1, (float)x.Item2)).ToArray();`
`88`	`90`	`}`
`89`	`91`
`90`	`92`	`IEnumerable<(string, Tensor)> test_function(OwnedIterator iterator)`
Original file line number	Diff line number	Diff line change
`@@ -51,7 +51,8 @@ public object output_size`
`51`	`51`	`}`
`52`	`52`	`else if (RNN._is_multiple_state(lastCell.state_size))`
`53`	`53`	`{`
`54`		`- return ((dynamic)Cells[-1].state_size)[0];`
	`54`	`+ // return ((dynamic)Cells[-1].state_size)[0];`
	`55`	`+ throw new NotImplementedException("");`
`55`	`56`	`}`
`56`	`57`	`else`
`57`	`58`	`{`