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- using System;
- using System.Collections;
- using System.Collections.Generic;
- using System.Numerics;
- using System.Text;
-
- namespace Tensorflow.NumPy
- {
- public partial class np
- {
- /// <summary>
- /// A convenient alias for None, useful for indexing arrays.
- /// </summary>
- /// <remarks>https://docs.scipy.org/doc/numpy-1.17.0/reference/arrays.indexing.html<br></br><br></br>https://stackoverflow.com/questions/42190783/what-does-three-dots-in-python-mean-when-indexing-what-looks-like-a-number</remarks>
- public static readonly Slice newaxis = new Slice(null, null, 1) { IsNewAxis = true };
-
- // https://docs.scipy.org/doc/numpy-1.16.0/user/basics.types.html
- #region data type
- public static readonly TF_DataType @bool = TF_DataType.TF_BOOL;
- public static readonly TF_DataType @char = TF_DataType.TF_INT8;
- public static readonly TF_DataType @byte = TF_DataType.TF_INT8;
- public static readonly TF_DataType uint8 = TF_DataType.TF_UINT8;
- public static readonly TF_DataType ubyte = TF_DataType.TF_UINT8;
- public static readonly TF_DataType int16 = TF_DataType.TF_INT16;
- public static readonly TF_DataType uint16 = TF_DataType.TF_UINT16;
- public static readonly TF_DataType int32 = TF_DataType.TF_INT32;
- public static readonly TF_DataType uint32 = TF_DataType.TF_UINT32;
- public static readonly TF_DataType int64 = TF_DataType.TF_INT64;
- public static readonly TF_DataType uint64 = TF_DataType.TF_UINT64;
- public static readonly TF_DataType float32 = TF_DataType.TF_FLOAT;
- public static readonly TF_DataType float64 = TF_DataType.TF_DOUBLE;
- public static readonly TF_DataType @double = TF_DataType.TF_DOUBLE;
- public static readonly TF_DataType @decimal = TF_DataType.TF_DOUBLE;
- public static readonly TF_DataType complex_ = TF_DataType.TF_COMPLEX;
- public static readonly TF_DataType complex64 = TF_DataType.TF_COMPLEX64;
- public static readonly TF_DataType complex128 = TF_DataType.TF_COMPLEX128;
- #endregion
-
- public static double nan => double.NaN;
- public static double NAN => double.NaN;
- public static double NaN => double.NaN;
- public static double pi => Math.PI;
- public static double e => Math.E;
- public static double euler_gamma => 0.57721566490153286060651209008240243d;
- public static double inf => double.PositiveInfinity;
- public static double infty => double.PositiveInfinity;
- public static double Inf => double.PositiveInfinity;
- public static double NINF => double.NegativeInfinity;
- public static double PINF => double.PositiveInfinity;
- public static double Infinity => double.PositiveInfinity;
- public static double infinity => double.PositiveInfinity;
-
- public static bool array_equal(NDArray a, NDArray b)
- => a.Equals(b);
-
- public static NDArray concatenate(NDArray[] arrays, int axis = 0)
- => throw new NotImplementedException("");
-
- public static NDArray frombuffer(byte[] bytes, string dtype)
- => throw new NotImplementedException("");
-
- public static bool allclose(NDArray a, NDArray b, double rtol = 1.0E-5, double atol = 1.0E-8,
- bool equal_nan = false) => throw new NotImplementedException("");
-
- public static class random
- {
- public static NDArray permutation(int x)
- {
- throw new NotImplementedException("");
- }
-
- public static void shuffle(NDArray nd)
- {
-
- }
-
- public static NDArray rand(params int[] shape)
- => throw new NotImplementedException("");
-
- public static NDArray randint(long x)
- => throw new NotImplementedException("");
-
- public static NDArray RandomState(int x)
- => throw new NotImplementedException("");
- }
-
- public static NpzDictionary<T> Load_Npz<T>(byte[] bytes)
- where T : class, IList, ICloneable, ICollection, IEnumerable, IStructuralComparable, IStructuralEquatable
- {
- throw new NotImplementedException("");
- }
- }
- }
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