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当我使用 tensorboardX 绘制数据丢失的图时，它告诉我：

AssertionError                            Traceback (most recent call last)
<ipython-input-76-73419a51fcc9> in <module>
----> 1 writer.add_scalar('resnet34_loss', loss)

F:\Program Files\Python\lib\site-packages\tensorboardX\writer.py in add_scalar(self, tag, scalar_value, global_step, walltime)
    403             scalar_value = workspace.FetchBlob(scalar_value)
    404         self._get_file_writer().add_summary(
--> 405             scalar(tag, scalar_value), global_step, walltime)
    406 
    407     def add_scalars(self, main_tag, tag_scalar_dict, global_step=None, walltime=None):

F:\Program Files\Python\lib\site-packages\tensorboardX\summary.py in scalar(name, scalar, collections)
    145     name = _clean_tag(name)
    146     scalar = make_np(scalar)
--> 147     assert(scalar.squeeze().ndim == 0), 'scalar should be 0D'
    148     scalar = float(scalar)
    149     return Summary(value=[Summary.Value(tag=name, simple_value=scalar)])

AssertionError: scalar should be 0D

我已经将损失从float变成np.array，并且我已经阅读了 tensorboardX 的文档，它告诉我add_scalar()函数必须输入标量数据并且我这样做了，但它向我显示了一个错误。谢谢你的帮助！

4

1 回答 1

0

我遇到了同样的问题，这是重现您的错误的最小示例，

writer = SummaryWriter(osp.join('runs', 'hello'))
loss = np.random.randn(10)
writer.add_scalar(tag='Checking range', scalar_value=loss)
writer.close()

这返回，

Traceback (most recent call last):

  File "untitled0.py", line 26, in <module>
    writer.add_scalar(tag='Checking range', scalar_value=loss)

  File "/home/melike/anaconda2/envs/pooling/lib/python3.6/site-packages/torch/utils/tensorboard/writer.py", line 346, in add_scalar
    scalar(tag, scalar_value), global_step, walltime)

  File "/home/melike/anaconda2/envs/pooling/lib/python3.6/site-packages/torch/utils/tensorboard/summary.py", line 248, in scalar
    assert(scalar.squeeze().ndim == 0), 'scalar should be 0D'

AssertionError: scalar should be 0D

如断言错误所示，scalar.squeeze().ndim应该有 0 维。让我们检查一下scalar_value，loss

print(loss.squeeze().ndim)

这输出

1

所以，我们找到了错误的原因，add_scalar期望squeeze操作后是 0-d 标量，我们给它一个 1-d 标量。PyTorch 文档的 Tensorboard页面有add_scalar示例。让我们将代码转换为该版本。

writer = SummaryWriter(osp.join('runs', 'hello'))
loss = np.random.randn(10)
for i, val in enumerate(loss):
    writer.add_scalar(tag='Checking range', scalar_value=val, global_step=i)
writer.close()

这是输出，

损失图

于 2021-04-07T08:27:48.647 回答