mirror of
https://github.com/hanzoai/jube-fork.git
synced 2026-10-30 18:33:33 +00:00
richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
527 lines
17 KiB
C#
527 lines
17 KiB
C#
// Accord Formats Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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namespace Accord.IO
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{
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using Accord.Math;
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.IO;
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using System.IO.Compression;
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using System.Linq;
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using System.Runtime.InteropServices;
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using System.Text;
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using Accord.Compat;
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using System.Threading.Tasks;
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#if !NET35 && !NET40
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/// <summary>
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/// Provides static methods to save and load files saved in NumPy's .npy format.
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/// </summary>
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///
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/// <seealso cref="NpzFormat"/>
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#else
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/// <summary>
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/// Provides static methods to save and load files saved in NumPy's .npy format.
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/// </summary>
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///
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#endif
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public static partial class NpyFormat
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{
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/// <summary>
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/// Loads an array of the specified type from a byte array.
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/// </summary>
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///
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/// <typeparam name="T">The type to be loaded from the npy-formatted file.</typeparam>
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/// <param name="bytes">The bytes that contain the matrix to be loaded.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(byte[] bytes)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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if (typeof(T).IsJagged())
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return LoadJagged(bytes).To<T>();
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return LoadMatrix(bytes).To<T>();
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}
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/// <summary>
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/// Loads an array of the specified type from a file in the disk.
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/// </summary>
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///
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/// <typeparam name="T">The type to be loaded from the npy-formatted file.</typeparam>
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/// <param name="bytes">The bytes that contain the matrix to be loaded.</param>
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/// <param name="value">The object to be read. This parameter can be used to avoid the
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/// need of specifying a generic argument to this function.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(byte[] bytes, out T value)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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return value = Load<T>(bytes);
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}
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/// <summary>
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/// Loads an array of the specified type from a file in the disk.
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/// </summary>
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///
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/// <typeparam name="T">The type to be loaded from the npy-formatted file.</typeparam>
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/// <param name="path">The path to the file containing the matrix to be loaded.</param>
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/// <param name="value">The object to be read. This parameter can be used to avoid the
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/// need of specifying a generic argument to this function.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(string path, out T value)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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return value = Load<T>(path);
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}
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/// <summary>
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/// Loads an array of the specified type from a stream.
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/// </summary>
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///
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/// <typeparam name="T">The type to be loaded from the npy-formatted file.</typeparam>
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/// <param name="stream">The stream containing the matrix to be loaded.</param>
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/// <param name="value">The object to be read. This parameter can be used to avoid the
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/// need of specifying a generic argument to this function.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(Stream stream, out T value)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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return value = Load<T>(stream);
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}
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/// <summary>
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/// Loads an array of the specified type from a file in the disk.
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/// </summary>
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///
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/// <param name="path">The path to the file containing the matrix to be loaded.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(string path)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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using (var stream = new FileStream(path, FileMode.Open))
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return Load<T>(stream);
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}
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/// <summary>
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/// Loads an array of the specified type from a stream.
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/// </summary>
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///
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/// <typeparam name="T">The type to be loaded from the npy-formatted file.</typeparam>
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/// <param name="stream">The stream containing the matrix to be loaded.</param>
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///
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/// <returns>The array to be returned.</returns>
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///
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public static T Load<T>(Stream stream)
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where T : class,
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#if !NETSTANDARD1_4
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ICloneable,
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#endif
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IList, ICollection, IEnumerable
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#if !NET35
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, IStructuralComparable, IStructuralEquatable
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#endif
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{
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if (typeof(T).IsJagged())
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return LoadJagged(stream).To<T>();
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return LoadMatrix(stream).To<T>();
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}
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/// <summary>
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/// Loads a multi-dimensional array from an array of bytes.
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/// </summary>
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///
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/// <param name="bytes">The bytes that contain the matrix to be loaded.</param>
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///
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/// <returns>A multi-dimensional array containing the values available in the given stream.</returns>
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///
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public static Array LoadMatrix(byte[] bytes)
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{
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using (var stream = new MemoryStream(bytes))
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return LoadMatrix(stream);
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}
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/// <summary>
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/// Loads a multi-dimensional array from a file in the disk.
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/// </summary>
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///
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/// <param name="path">The path to the file containing the matrix to be loaded.</param>
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///
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/// <returns>A multi-dimensional array containing the values available in the given stream.</returns>
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///
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public static Array LoadMatrix(string path)
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{
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using (var stream = new FileStream(path, FileMode.Open))
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return LoadMatrix(stream);
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}
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/// <summary>
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/// Loads a jagged array from an array of bytes.
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/// </summary>
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///
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/// <param name="bytes">The bytes that contain the matrix to be loaded.</param>
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///
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/// <returns>A jagged array containing the values available in the given stream.</returns>
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///
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public static Array LoadJagged(byte[] bytes)
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{
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using (var stream = new MemoryStream(bytes))
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return LoadJagged(stream);
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}
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/// <summary>
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/// Loads a jagged array from a file in the disk.
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/// </summary>
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///
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/// <param name="path">The path to the file containing the matrix to be loaded.</param>
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///
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/// <returns>A jagged array containing the values available in the given stream.</returns>
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///
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public static Array LoadJagged(string path)
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{
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using (var stream = new FileStream(path, FileMode.Open))
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return LoadJagged(stream);
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}
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/// <summary>
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/// Loads a multi-dimensional array from a stream.
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/// </summary>
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///
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/// <param name="stream">The stream containing the matrix to be loaded.</param>
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///
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/// <returns>A multi-dimensional array containing the values available in the given stream.</returns>
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///
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public static Array LoadMatrix(Stream stream)
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{
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using (var reader = new BinaryReader(stream, System.Text.Encoding.ASCII
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#if !NET35 && !NET40
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, leaveOpen: true
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#endif
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))
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{
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int bytes;
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Type type;
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int[] shape;
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if (!parseReader(reader, out bytes, out type, out shape))
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throw new FormatException();
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Array matrix = Matrix.Zeros(type, shape);
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if (type == typeof(String))
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return readStringMatrix(reader, matrix, bytes, type, shape);
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return readValueMatrix(reader, matrix, bytes, type, shape);
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}
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}
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/// <summary>
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/// Loads a jagged array from a stream.
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/// </summary>
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///
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/// <param name="stream">The stream containing the matrix to be loaded.</param>
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/// <param name="trim">Pass true to remove null or empty elements from the loaded array.</param>
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///
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/// <returns>A jagged array containing the values available in the given stream.</returns>
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///
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public static Array LoadJagged(Stream stream, bool trim = true)
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{
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using (var reader = new BinaryReader(stream, System.Text.Encoding.ASCII
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#if !NET35 && !NET40
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, leaveOpen: true
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#endif
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))
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{
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int bytes;
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Type type;
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int[] shape;
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if (!parseReader(reader, out bytes, out type, out shape))
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throw new FormatException();
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Array matrix = Jagged.Zeros(type, shape);
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if (type == typeof(String))
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{
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Array result = readStringMatrix(reader, matrix, bytes, type, shape);
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if (trim)
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return result.Trim();
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return result;
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}
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return readValueJagged(reader, matrix, bytes, type, shape);
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}
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}
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private static Array readValueMatrix(BinaryReader reader, Array matrix, int bytes, Type type, int[] shape)
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{
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int total = 1;
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for (int i = 0; i < shape.Length; i++)
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total *= shape[i];
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var buffer = new byte[bytes * total];
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reader.Read(buffer, 0, buffer.Length);
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Buffer.BlockCopy(buffer, 0, matrix, 0, buffer.Length);
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return matrix;
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}
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private static Array readValueJagged(BinaryReader reader, Array matrix, int bytes, Type type, int[] shape)
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{
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int last = shape[shape.Length - 1];
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byte[] buffer = new byte[bytes * last];
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int[] firsts = new int[shape.Length - 1];
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for (int i = 0; i < firsts.Length; i++)
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firsts[i] = -1;
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foreach (var p in matrix.GetIndices(deep: true))
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{
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bool changed = false;
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for (int i = 0; i < firsts.Length; i++)
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{
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if (firsts[i] != p[i])
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{
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firsts[i] = p[i];
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changed = true;
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}
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}
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if (!changed)
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continue;
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Array arr = (Array)matrix.GetValue(deep: true, indices: firsts);
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reader.Read(buffer, 0, buffer.Length);
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Buffer.BlockCopy(buffer, 0, arr, 0, buffer.Length);
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}
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return matrix;
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}
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private static Array readStringMatrix(BinaryReader reader, Array matrix, int bytes, Type type, int[] shape)
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{
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var buffer = new byte[bytes];
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unsafe
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{
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fixed (byte* b = buffer)
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{
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foreach (var p in matrix.GetIndices(deep: true))
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{
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reader.Read(buffer, 0, bytes);
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if (buffer[0] == byte.MinValue)
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{
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bool isNull = true;
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for (int i = 1; i < buffer.Length; i++)
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{
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if (buffer[i] != byte.MaxValue)
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{
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isNull = false;
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break;
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}
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}
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if (isNull)
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{
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matrix.SetValue(value: null, deep: true, indices: p);
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continue;
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}
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}
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#if NETSTANDARD1_4
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String s = new String((char*)b);
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#else
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String s = new String((sbyte*)b);
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#endif
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matrix.SetValue(value: s, deep: true, indices: p);
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}
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}
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}
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return matrix;
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}
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private static bool parseReader(BinaryReader reader, out int bytes, out Type t, out int[] shape)
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{
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bytes = 0;
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t = null;
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shape = null;
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// The first 6 bytes are a magic string: exactly "x93NUMPY"
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if (reader.ReadChar() != 63) return false;
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if (reader.ReadChar() != 'N') return false;
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if (reader.ReadChar() != 'U') return false;
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if (reader.ReadChar() != 'M') return false;
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if (reader.ReadChar() != 'P') return false;
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if (reader.ReadChar() != 'Y') return false;
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byte major = reader.ReadByte(); // 1
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byte minor = reader.ReadByte(); // 0
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if (major != 1 || minor != 0)
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throw new NotSupportedException();
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ushort len = reader.ReadUInt16();
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string header = new String(reader.ReadChars(len));
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string mark = "'descr': '";
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int s = header.IndexOf(mark) + mark.Length;
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int e = header.IndexOf("'", s + 1);
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string type = header.Substring(s, e - s);
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bool? isLittleEndian;
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t = GetType(type, out bytes, out isLittleEndian);
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if (isLittleEndian.HasValue && isLittleEndian.Value == false)
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throw new Exception();
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mark = "'fortran_order': ";
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s = header.IndexOf(mark) + mark.Length;
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e = header.IndexOf(",", s + 1);
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bool fortran = bool.Parse(header.Substring(s, e - s));
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if (fortran)
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throw new Exception();
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mark = "'shape': (";
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s = header.IndexOf(mark) + mark.Length;
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e = header.IndexOf(")", s + 1);
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shape = header.Substring(s, e - s).Split(',').Select(Int32.Parse).ToArray();
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return true;
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}
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private static Type GetType(string dtype, out int bytes, out bool? isLittleEndian)
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{
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isLittleEndian = IsLittleEndian(dtype);
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bytes = Int32.Parse(dtype.Substring(2));
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string typeCode = dtype.Substring(1);
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if (typeCode == "b1")
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return typeof(bool);
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if (typeCode == "i1")
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return typeof(SByte);
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if (typeCode == "i2")
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return typeof(Int16);
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if (typeCode == "i4")
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return typeof(Int32);
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if (typeCode == "i8")
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return typeof(Int64);
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if (typeCode == "u1")
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return typeof(Byte);
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if (typeCode == "u2")
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return typeof(UInt16);
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if (typeCode == "u4")
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return typeof(UInt32);
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if (typeCode == "u8")
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return typeof(UInt64);
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if (typeCode == "f4")
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return typeof(Single);
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if (typeCode == "f8")
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return typeof(Double);
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if (typeCode.StartsWith("S"))
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return typeof(String);
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throw new NotSupportedException();
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}
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private static bool? IsLittleEndian(string type)
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{
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bool? littleEndian = null;
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switch (type[0])
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{
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case '<':
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littleEndian = true;
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break;
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case '>':
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littleEndian = false;
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break;
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case '|':
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littleEndian = null;
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break;
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default:
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throw new Exception();
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}
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return littleEndian;
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}
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}
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}
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