forked from SciSharp/TensorFlow.NET
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathMNIST.cs
More file actions
73 lines (61 loc) · 2.33 KB
/
Copy pathMNIST.cs
File metadata and controls
73 lines (61 loc) · 2.33 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
/*****************************************************************************
Copyright 2020 Haiping Chen. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
******************************************************************************/
using Tensorflow.NumPy;
using System;
using System.IO;
using Tensorflow.Keras.Utils;
namespace Tensorflow.Keras.Datasets
{
public class Mnist
{
string origin_folder = "https://storage.googleapis.com/tensorflow/tf-keras-datasets/";
string file_name = "mnist.npz";
/// <summary>
/// Loads the [MNIST dataset](http://yann.lecun.com/exdb/mnist/).
/// </summary>
/// <returns></returns>
public DatasetPass load_data()
{
var file = Download();
var bytes = File.ReadAllBytes(file);
var datax = LoadX(bytes);
var datay = LoadY(bytes);
return new DatasetPass
{
Train = (datax.Item1, datay.Item1),
Test = (datax.Item2, datay.Item2)
};
}
(NDArray, NDArray) LoadX(byte[] bytes)
{
var x = np.Load_Npz<byte[,,]>(bytes);
return (x["x_train.npy"], x["x_test.npy"]);
}
(NDArray, NDArray) LoadY(byte[] bytes)
{
var y = np.Load_Npz<byte[]>(bytes);
return (y["y_train.npy"], y["y_test.npy"]);
}
string Download()
{
var fileSaveTo = Path.Combine(Path.GetTempPath(), file_name);
if (File.Exists(fileSaveTo))
{
Binding.tf_output_redirect.WriteLine($"The file {fileSaveTo} already exists");
return fileSaveTo;
}
Web.Download(origin_folder + file_name, Path.GetTempPath(), file_name);
return fileSaveTo;
}
}
}