[原创] 在树莓派上跑起来TensorBoard

本文软硬件环境：
树莓派：3代 Model B V1.2
OS：Arch Linux ARM，32bit

TensorBoard是Tensorflow的可视化工具。当我们用这篇文章里的方法在树莓派上安装好Tensorflow之后，TensorBoard自然就装好了。于是，下面只剩下怎么启动它的问题。
以下是一个例子。

首先，我们从TensorFlow的官方Github里下载这个文件：

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/mnist/mnist_with_summaries.py

它实现了一个模型训练的过程，并且在模型训练的过程中，将TensorBoard所需的数据文件，输出到了 /tmp/tensorflow/mnist/logs/mnist_with_summaries 这个目录下（写死在 mnist_with_summaries.py 文件中，为了简单无需修改）。
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之后我们把这个模型训练的程序跑起来：

python2 mnist_with_summaries.py

然后程序会自动去下载MNIST数据，并开始训练模型：

Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.

Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz

Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.

Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz

Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.

Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz

Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.

Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz

Accuracy at step 0: 0.1114

Accuracy at step 10: 0.6652

Accuracy at step 20: 0.8119

Accuracy at step 30: 0.8533

Accuracy at step 40: 0.868

Accuracy at step 50: 0.8723

Accuracy at step 60: 0.8779

Accuracy at step 70: 0.879

Accuracy at step 80: 0.8817

Accuracy at step 90: 0.8876

Adding run metadata for 99

Accuracy at step 100: 0.896

Accuracy at step 110: 0.9061

Accuracy at step 120: 0.9116

Accuracy at step 130: 0.9167

Accuracy at step 140: 0.9216

Accuracy at step 150: 0.915

Accuracy at step 160: 0.9246

Accuracy at step 170: 0.9267

Accuracy at step 180: 0.9215

Accuracy at step 190: 0.9207

Adding run metadata for 199

Accuracy at step 200: 0.9287

Accuracy at step 210: 0.933

Accuracy at step 220: 0.9307

Accuracy at step 230: 0.9308

......

tensorboard --logdir=/tmp/tensorflow/mnist/logs/mnist_with_summaries

其中，--logdir参数指定的目录就是 mnist_with_summaries.py 程序里用 --log_dir 参数指定的那个路径，TensorBoard会从这个路径下读取数据并可视化展示在web页面中。
过一会就会看到命令行提示：

Starting TensorBoard 41 on port 6006

(You can navigate to http://10.0.0.2:6006)

所以现在打开浏览器，访问这个地址，就可以看到图了：

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