TensorInfo initialization improved, more checks added

Author: Sergio0694

NeuralNetwork.NET/APIs/Structs/ConvolutionInfo.cs

@@ -92,6 +92,7 @@ internal TensorInfo GetForwardOutputTensorInfo(in TensorInfo input, (int X, int
             int
                 h = (input.Height - field.X + 2 * VerticalPadding) / VerticalStride + 1,
                 w = (input.Width - field.Y + 2 * HorizontalPadding) / HorizontalStride + 1;
+            if (h <= 0 || w <= 0) throw new InvalidOperationException("The input convolution kernels can't be applied to the input tensor shape");
             return new TensorInfo(h, w, kernels);
         }
 

NeuralNetwork.NET/APIs/Structs/PoolingInfo.cs

@@ -99,6 +99,7 @@ internal TensorInfo GetForwardOutputTensorInfo(in TensorInfo input)
             int
                 h = (input.Height - WindowHeight + 2 * VerticalPadding) / VerticalStride + 1,
                 w = (input.Width - WindowWidth + 2 * HorizontalPadding) / HorizontalStride + 1;
+            if (h <= 0 || w <= 0) throw new InvalidOperationException("The input tensor shape is not valid to apply the current pooling operation");
             return new TensorInfo(h, w, input.Channels);
         }
 

NeuralNetwork.NET/APIs/Structs/TensorInfo.cs

@@ -40,7 +40,6 @@ namespace NeuralNetworkNET.APIs.Structs
         [JsonProperty(nameof(Size), Order = 4)]
         public int Size
         {
-            [Pure]
             [MethodImpl(MethodImplOptions.AggressiveInlining)]
             get => Height * Width * Channels;
         }
@@ -50,18 +49,27 @@ public int Size
         /// </summary>
         public int SliceSize
         {
-            [Pure]
             [MethodImpl(MethodImplOptions.AggressiveInlining)]
             get => Height * Width;
         }
 
+        /// <summary>
+        /// Gets whether the current <see cref="Tensor"/> instance is invalid (empty or with invalid parameters)
+        /// </summary>
+        public bool IsEmptyOrInvalid
+        {
+            [MethodImpl(MethodImplOptions.AggressiveInlining)]
+            get => Height <= 0 || Width <= 0 || Channels <= 0;
+        }
+
         #endregion
 
         #region Constructors
 
         internal TensorInfo(int height, int width, int channels)
         {
-            if (height * width <= 0) throw new ArgumentException("The height and width of the kernels must be positive values");
+            if (height <= 0 || width <= 0) throw new ArgumentException("The height and width of the kernels must be positive values");
+            if (channels <= 0) throw new ArgumentException("The number of channels must be positive");
             Height = height;
             Width = width;
             Channels = channels >= 1 ? channels :  throw new ArgumentOutOfRangeException(nameof(channels), "The number of channels must be at least equal to 1");

NeuralNetwork.NET/Networks/Layers/Abstract/NetworkLayerBase.cs

@@ -1,4 +1,5 @@
-using System.IO;
+using System;
+using System.IO;
 using System.Runtime.CompilerServices;
 using JetBrains.Annotations;
 using NeuralNetworkNET.APIs.Enums;
@@ -58,8 +59,8 @@ public ref readonly TensorInfo OutputInfo
 
         protected NetworkLayerBase(in TensorInfo input, in TensorInfo output, ActivationFunctionType activation)
         {
-            _InputInfo = input;
-            _OutputInfo = output;
+            _InputInfo = input.IsEmptyOrInvalid ? throw new ArgumentException("The layer input info is not valid", nameof(input)) : input;
+            _OutputInfo = output.IsEmptyOrInvalid ? throw new ArgumentException("The layer output info is not valid", nameof(output)) : output;
             ActivationFunctionType = activation;
             ActivationFunctions = ActivationFunctionProvider.GetActivations(activation);
         }