关于add_scalar()的TensorboardX输入问题
关于add_scalar()的TensorboardX输入问题
提问于 2020-06-26 21:38:58
当我使用tensorboardX绘制我的数据丢失情况时，它向我显示：
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我已经把float中的损失转换成了np.array，并且我读了tensorboardX的文档，它告诉我add_scalar()函数必须输入标量数据，我这样做了，但它显示了一个错误。谢谢你的帮忙!
回答 1
Stack Overflow用户
发布于 2021-04-07 16:27:49
我也有同样的问题，这里有一个最小的样本来重现你的错误，
writer = SummaryWriter(osp.join('runs', 'hello'))
loss = np.random.randn(10)
writer.add_scalar(tag='Checking range', scalar_value=loss)
writer.close()这会返回
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应该是0维的。让我们检查一下我们的scalar_value，它是loss，
print(loss.squeeze().ndim)下面的输出
1因此，我们找到了错误的原因，在squeeze操作之后，add_scalar需要0-d标量，我们给它一个1-d标量。PyTorch文档的Tensorboard页面包含add_scalar示例。让我们将我们的代码转换为该版本。
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，
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/62596016
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