Remove Range class due to conflict with .net 5.

Oceania2018 · Oceania2018 · commit 11fdd9a8ee69 · 2021-05-22T22:57:45.000-05:00
diff --git a/src/TensorFlowNET.Core/Operations/Operation.Implicit.cs b/src/TensorFlowNET.Core/Operations/Operation.Implicit.cs
@@ -31,8 +31,6 @@ public static implicit operator IntPtr(Operation op)
             => op._handle;
         public static implicit operator Tensor(Operation op)
             => op.output;
-        public static implicit operator RefVariable(Operation op)
-            => new RefVariable(op);
 
         public override string ToString()
         {
diff --git a/src/TensorFlowNET.Core/Operations/embedding_ops.cs b/src/TensorFlowNET.Core/Operations/embedding_ops.cs
@@ -21,37 +21,6 @@ namespace Tensorflow
 {
     public class embedding_ops
     {
-        /// <summary>
-        /// Helper function for embedding_lookup and _compute_sampled_logits.
-        /// </summary>
-        /// <param name="params"></param>
-        /// <param name="ids"></param>
-        /// <param name="partition_strategy"></param>
-        /// <param name="name"></param>
-        /// <returns></returns>
-        public static Tensor _embedding_lookup_and_transform(RefVariable @params,
-                Tensor ids,
-                string partition_strategy = "mod",
-                string name = null,
-                string max_norm = null)
-        {
-            return tf_with(ops.name_scope(name, "embedding_lookup", new { @params, ids }), scope =>
-            {
-                name = scope;
-                int np = 1;
-                ids = ops.convert_to_tensor(ids, name: "ids");
-                if (np == 1)
-                {
-                    var gather = array_ops.gather(@params, ids, name: name);
-                    var result = _clip(gather, ids, max_norm);
-
-                    return array_ops.identity(result);
-                }
-
-                throw new NotImplementedException("_embedding_lookup_and_transform");
-            });
-        }
-
         /// <summary>
         /// Helper function for embedding_lookup and _compute_sampled_logits.
         /// </summary>
diff --git a/src/TensorFlowNET.Keras/Engine/Model.Compile.cs b/src/TensorFlowNET.Keras/Engine/Model.Compile.cs
@@ -10,9 +10,16 @@ public partial class Model
         LossesContainer compiled_loss;
         MetricsContainer compiled_metrics;
 
-        public void compile(ILossFunc loss, OptimizerV2 optimizer, string[] metrics)
+        public void compile(OptimizerV2 optimizer = null, 
+            ILossFunc loss = null, 
+            string[] metrics = null)
         {
-            this.optimizer = optimizer;
+            this.optimizer = optimizer ?? new RMSprop(new RMSpropArgs
+            {
+            });
+
+            this.loss = loss ?? new MeanSquaredError();
+
             compiled_loss = new LossesContainer(loss, output_names: output_names);
             compiled_metrics = new MetricsContainer(metrics, output_names: output_names);
 
@@ -22,7 +29,6 @@ public void compile(ILossFunc loss, OptimizerV2 optimizer, string[] metrics)
             // Initialize cache attrs.
             _reset_compile_cache();
             _is_compiled = true;
-            this.loss = loss;
         }
 
         public void compile(string optimizer, string loss, string[] metrics)
diff --git a/src/TensorFlowNET.Keras/Layers/LayersApi.cs b/src/TensorFlowNET.Keras/Layers/LayersApi.cs
@@ -518,6 +518,18 @@ public Tensors Input(TensorShape shape,
             return input_layer.InboundNodes[0].Outputs;
         }
 
+        public InputLayer InputLayer(TensorShape input_shape,
+            string name = null,
+            bool sparse = false,
+            bool ragged = false)
+            => new InputLayer(new InputLayerArgs
+            {
+                InputShape = input_shape,
+                Name = name,
+                Sparse = sparse,
+                Ragged = ragged
+            });
+
         /// <summary>
         /// Max pooling operation for 1D temporal data.
         /// </summary>
diff --git a/src/TensorFlowNet.Benchmarks/Tensorflow.Benchmark.csproj b/src/TensorFlowNet.Benchmarks/Tensorflow.Benchmark.csproj
@@ -36,7 +36,7 @@
 
   <ItemGroup>
     <PackageReference Include="BenchmarkDotNet" Version="0.12.1" />
-    <PackageReference Include="SciSharp.TensorFlow.Redist-Windows-GPU" Version="2.3.1" />
+    <PackageReference Include="SciSharp.TensorFlow.Redist-Windows-GPU" Version="2.5.0" />
   </ItemGroup>
 
   <ItemGroup>
diff --git a/test/TensorFlowNET.Keras.UnitTest/Layers/LayersTest.cs b/test/TensorFlowNET.Keras.UnitTest/Layers/LayersTest.cs
@@ -1,7 +1,8 @@
 ﻿using Microsoft.VisualStudio.TestTools.UnitTesting;
 using NumSharp;
+using System.Collections.Generic;
 using Tensorflow;
-using Tensorflow.Operations.Initializers;
+using Tensorflow.Keras;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
@@ -13,6 +14,18 @@ namespace TensorFlowNET.Keras.UnitTest
     [TestClass]
     public class LayersTest : EagerModeTestBase
     {
+        // [TestMethod]
+        public void InputLayer()
+        {
+            var model = keras.Sequential(new List<ILayer>
+            {
+              keras.layers.InputLayer(input_shape: 4),
+              keras.layers.Dense(8)
+            });
+            model.compile(optimizer: keras.optimizers.RMSprop(0.001f));
+            model.fit(np.zeros((10, 4)), np.ones((10, 8)));
+        }
+
         [TestMethod]
         public void Sequential()
         {
diff --git a/test/TensorFlowNET.Keras.UnitTest/Range.cs b/test/TensorFlowNET.Keras.UnitTest/Range.cs
diff --git a/test/TensorFlowNET.Keras.UnitTest/RuntimeHelpers.cs b/test/TensorFlowNET.Keras.UnitTest/RuntimeHelpers.cs

Original file line number	Diff line number	Diff line change
`@@ -31,8 +31,6 @@ public static implicit operator IntPtr(Operation op)`
`31`	`31`	`=> op._handle;`
`32`	`32`	`public static implicit operator Tensor(Operation op)`
`33`	`33`	`=> op.output;`
`34`		`- public static implicit operator RefVariable(Operation op)`
`35`		`- => new RefVariable(op);`
`36`	`34`
`37`	`35`	`public override string ToString()`
`38`	`36`	`{`