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- using System;
- using System.Collections;
- using System.Collections.Generic;
- using System.Numerics;
- using System.Text;
- using static Tensorflow.Binding;
-
- namespace Tensorflow.NumPy
- {
- public partial class np
- {
- public static NDArray array(Array data)
- => new NDArray(data);
-
- public static NDArray array<T>(params T[] data)
- where T : unmanaged
- => new NDArray(data);
-
- public static NDArray arange<T>(T end)
- where T : unmanaged
- => new NDArray(tf.range(default(T), limit: end));
-
- public static NDArray arange<T>(T start, T? end = null, T? step = null)
- where T : unmanaged
- => new NDArray(tf.range(start, limit: end, delta: step));
-
- public static NDArray empty(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
- => new NDArray(tf.zeros(shape, dtype: dtype));
-
- public static NDArray eye(int N, int? M = null, int k = 0, TF_DataType dtype = TF_DataType.TF_DOUBLE)
- => tf.numpy.eye(N, M: M, k: k, dtype: dtype);
-
- public static NDArray full<T>(Shape shape, T fill_value)
- => new NDArray(tf.fill(tf.constant(shape), fill_value));
-
- public static NDArray linspace<T>(T start, T stop, int num = 50, bool endpoint = true, bool retstep = false,
- TF_DataType dtype = TF_DataType.TF_DOUBLE, int axis = 0) where T : unmanaged
- => tf.numpy.linspace(start, stop, num: num, endpoint: endpoint, retstep: retstep, dtype: dtype, axis: axis);
-
- public static (NDArray, NDArray) meshgrid<T>(T x, T y, bool copy = true, bool sparse = false)
- => tf.numpy.meshgrid(new[] { x, y }, copy: copy, sparse: sparse);
-
- public static NDArray ones(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
- => new NDArray(tf.ones(shape, dtype: dtype));
-
- public static NDArray ones_like(NDArray a, Type dtype = null)
- => throw new NotImplementedException("");
-
- public static NDArray zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
- => new NDArray(tf.zeros(shape, dtype: dtype));
- }
- }
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