Add EinsumDense support and simply test it

Author: Andy-Elizabeth-mouse

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

@@ -44,7 +44,7 @@ public List<T> get_collection<T>(string key, string scope = "")
         /// When eager execution is enabled, code inside an init_scope block runs with
         /// eager execution enabled even when tracing a `tf.function`. 
         /// </summary>
-        public void init_scope()
+        public ops.NameScope init_scope()
             => ops.init_scope();
 
         /// <summary>

src/TensorFlowNET.Core/Keras/ArgsDefinition/Attention/EinsumDenseArgs.cs

@@ -0,0 +1,66 @@
+using System;
+using static Tensorflow.Binding;
+
+namespace Tensorflow.Keras.ArgsDefinition
+{
+    public class EinsumDenseArgs : LayerArgs
+    {
+        /// <summary>
+        /// An equation describing the einsum to perform. This equation must
+        /// be a valid einsum string of the form `ab,bc->ac`, `...ab,bc->...ac`, or
+        /// `ab...,bc->ac...` where 'ab', 'bc', and 'ac' can be any valid einsum axis
+        /// expression sequence.
+        /// </summary>
+        public string Equation { get; set; }
+
+        /// <summary>
+        /// The expected shape of the output tensor (excluding the batch
+        /// dimension and any dimensions represented by ellipses). You can specify
+        /// None for any dimension that is unknown or can be inferred from the input
+        /// shape.
+        /// </summary>
+        public Shape OutputShape { get; set; }
+
+        /// <summary>
+        /// A string containing the output dimension(s) to apply a bias to.
+        /// Each character in the `bias_axes` string should correspond to a character
+        /// in the output portion of the `equation` string.
+        /// </summary>
+        public string BiasAxes { get; set; } = null;
+
+        /// <summary>
+        /// Activation function to use.
+        /// </summary>
+        public Activation Activation { get; set; }
+
+        /// <summary>
+        /// Initializer for the `kernel` weights matrix.
+        /// </summary>
+        public IInitializer KernelInitializer { get; set; } = tf.glorot_uniform_initializer;
+
+        /// <summary>
+        /// Initializer for the bias vector.
+        /// </summary>
+        public IInitializer BiasInitializer { get; set; } = tf.zeros_initializer;
+
+        /// <summary>
+        /// Regularizer function applied to the `kernel` weights matrix.
+        /// </summary>
+        public IRegularizer KernelRegularizer { get; set; }
+
+        /// <summary>
+        /// Regularizer function applied to the bias vector.
+        /// </summary>
+        public IRegularizer BiasRegularizer { get; set; }
+
+        /// <summary>
+        /// Constraint function applied to the `kernel` weights matrix.
+        /// </summary>
+        public Action KernelConstraint { get; set; }
+
+        /// <summary>
+        /// Constraint function applied to the bias vector.
+        /// </summary>
+        public Action BiasConstraint { get; set; }
+    }
+}

src/TensorFlowNET.Core/Keras/ArgsDefinition/Attention/MultiHeadAttentionArgs.cs

@@ -0,0 +1,22 @@
+using System;
+using static Tensorflow.Binding;
+
+namespace Tensorflow.Keras.ArgsDefinition
+{
+    public class MultiHeadAttentionArgs : LayerArgs
+    {
+        public int NumHeads { get; set; }
+        public int KeyDim { get; set; }
+        public int? ValueDim { get; set; } = null;
+        public float Dropout { get; set; } = 0f;
+        public bool UseBias { get; set; } = true;
+        public Shape OutputShape { get; set; } = null;
+        public Shape AttentionAxis { get; set; } = null;
+        public IInitializer KernelInitializer { get; set; } = tf.glorot_uniform_initializer;
+        public IInitializer BiasInitializer { get; set; } = tf.zeros_initializer;
+        public IRegularizer KernelRegularizer { get; set; } = null;
+        public IRegularizer BiasRegularizer { get; set; } = null;
+        public Action KernelConstraint { get; set; } = null;
+        public Action BiasConstraint { get; set; } = null;
+    }
+}