pytorch学习笔记之tensorboardX的使用

「爱情、让人受尽委屈。」 2022-12-20 12:48 372阅读 0赞

使用tensorflow训练模型的过程中需要关注学习曲线避免模型过拟合，借助tensorboard可以非常方便地对训练过程中的各种数据进行可视化分析；幸运的是，借助tensorboardX我们也可以在pytorch中得到相同的可视化体验（虽然在pytorch下使用tensorboardX，但其内核是 tensorflow里面的board，所以安装之前得先安装 tensorflow）

# 1 安装必备的工具 #

pip install tensorboardX
    pip install tensorboard
    pip install tensorflow

# 2 在代码中使用举例 #

在使用的时候需要创建一个SummaryWriter的实例：

from tensorboardX import SummaryWriter
    
    # 定义一个SummaryWriter的实例，使用writer记录的数据将保存在Result这个文件夹内
    writer = SummaryWriter('./Result')
    
    """
    使用add_scalar添加数字记录
    
    tag (string): 数据名称，不同名称的数据使用不同曲线展示
    scalar_value (float): 数字常量值
    global_step (int, optional): 训练的 step
    walltime (float, optional): 记录发生的时间，默认为 time.time()
    """
    writer.add_scalar(tag_name="tag_name", scaler_value=value, global_step=cur_step)

SummaryWriter有很多的参数可以配置，常用的有：

*  logdir：指定数据保存的位置，如果没有指定这个参数将会在当前目录下新建一个runs文件夹，结果会自动保存在这里
 *  comment：如果没有指定logdir，comment字段的内容将会被自动添加到日志文件的末尾；如果制定了logdir，这个参数无效

具体的可以看下面的文档：

SummaryWriter(
        logdir=None,
        comment='',
        purge_step=None,
        max_queue=10,
        flush_secs=120,
        filename_suffix='',
        write_to_disk=True,
        log_dir=None,
        **kwargs,
    )
    
    Docstring:     
    Writes entries directly to event files in the logdir to be
    consumed by TensorBoard.
    
    The `SummaryWriter` class provides a high-level API to create an event file
    in a given directory and add summaries and events to it. The class updates the
    file contents asynchronously. This allows a training program to call methods
    to add data to the file directly from the training loop, without slowing down
    training.
    Init docstring:
    Creates a `SummaryWriter` that will write out events and summaries
    to the event file.
    
    Args:
        logdir (string): Save directory location. Default is
          runs/**CURRENT_DATETIME_HOSTNAME**, which changes after each run.
          Use hierarchical folder structure to compare
          between runs easily. e.g. pass in 'runs/exp1', 'runs/exp2', etc.
          for each new experiment to compare across them.
        comment (string): Comment logdir suffix appended to the default
          ``logdir``. If ``logdir`` is assigned, this argument has no effect.
        purge_step (int):
          When logging crashes at step :math:`T+X` and restarts at step :math:`T`,
          any events whose global_step larger or equal to :math:`T` will be
          purged and hidden from TensorBoard.
          Note that crashed and resumed experiments should have the same ``logdir``.
        max_queue (int): Size of the queue for pending events and
          summaries before one of the 'add' calls forces a flush to disk.
          Default is ten items.
        flush_secs (int): How often, in seconds, to flush the
          pending events and summaries to disk. Default is every two minutes.
        filename_suffix (string): Suffix added to all event filenames in
          the logdir directory. More details on filename construction in
          tensorboard.summary.writer.event_file_writer.EventFileWriter.
        write_to_disk (boolean):
          If pass `False`, SummaryWriter will not write to disk.
    
    Examples::
    
        from tensorboardX import SummaryWriter
    
        # create a summary writer with automatically generated folder name.
        writer = SummaryWriter()
        # folder location: runs/May04_22-14-54_s-MacBook-Pro.local/
    
        # create a summary writer using the specified folder name.
        writer = SummaryWriter("my_experiment")
        # folder location: my_experiment
    
        # create a summary writer with comment appended.
        writer = SummaryWriter(comment="LR_0.1_BATCH_16")
        # folder location: runs/May04_22-14-54_s-MacBook-Pro.localLR_0.1_BATCH_16/

使用下面的完整例子体验一下：

运行下面的代码之后会在当前目录下得到一个runs文件夹，复制这个路径：

from tensorboardX import SummaryWriter
    import random
    
    writer = SummaryWriter('./runs/examples')
    
    for i in range(100):
        writer.add_scalar('example1', i**2, global_step=i)
        writer.add_scalar('example2', random.random(), global_step=i)

之后到控制台输入：

tensorboard --logdir=YOUR_PATH

一切正常的话，会得到一个local\_host的地址如这样：[http://desktop-chh6vvf:6006/][http_desktop-chh6vvf_6006] 或者 [http://localhost:6006/][http_localhost_6006]，复制这个地址到浏览器就能看到这样的界面了：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI2ODIyMDI5_size_16_color_FFFFFF_t_70][]

在这里可以点开你关注的数据观察~

# 3 其他功能 #

除此之外，还可以使用add\_image()，add\_histogram()，add\_graph()，add\_embedding()等在tensorboard查看图片，直方图，模型结构图，emedding结果等。

如运行下面的代码将会得到下图的结构：

class MultipleInput(nn.Module):
        def __init__(self):
            super(MultipleInput, self).__init__()
            self.Linear_1 = nn.Linear(3, 5)
    
    
        def forward(self, x, y):
            return self.Linear_1(x+y)
    
    with SummaryWriter(comment='MultipleInput') as w:
        w.add_graph(MultipleInput(), (torch.zeros(1, 3), torch.zeros(1, 3)), True)

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI2ODIyMDI5_size_16_color_FFFFFF_t_70 1][]

更多的代码可以看TensorboardX官方示例代码：[https://github.com/lanpa/tensorboardX/blob/master/examples/demo\_graph.py][https_github.com_lanpa_tensorboardX_blob_master_examples_demo_graph.py]

参考:

[https://blog.csdn.net/bigbennyguo/article/details/87956434][https_blog.csdn.net_bigbennyguo_article_details_87956434]

[https://zhuanlan.zhihu.com/p/54947519][https_zhuanlan.zhihu.com_p_54947519]

[http_desktop-chh6vvf_6006]: http://desktop-chh6vvf:6006/#scalars
[http_localhost_6006]: http://localhost:6006/
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI2ODIyMDI5_size_16_color_FFFFFF_t_70]: /images/20221120/1a1bd370688241d39ede6a5c3046a43e.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI2ODIyMDI5_size_16_color_FFFFFF_t_70 1]: /images/20221120/53081b3d431149ce8b004c308e2bf909.png
[https_github.com_lanpa_tensorboardX_blob_master_examples_demo_graph.py]: https://github.com/lanpa/tensorboardX/blob/master/examples/demo_graph.py
[https_blog.csdn.net_bigbennyguo_article_details_87956434]: https://blog.csdn.net/bigbennyguo/article/details/87956434
[https_zhuanlan.zhihu.com_p_54947519]: https://zhuanlan.zhihu.com/p/54947519