weight tensor should be defined either for all 3 classes or no classes but got weight tensor of shape: [1 x 2] at C:/cb/pytorch_1000000000000/work/aten/src\THCUNN/generic/ClassNLLCriterion.cu:44
时间: 2024-01-24 12:02:34 浏览: 66
这个错误通常是由于使用 `weight` 参数时出现的维度不匹配导致的。`weight` 参数应该是一个形状为 `[num_classes]` 的张量,其中 `num_classes` 是分类问题的类别数。在你的情况下,你提供的 `weight` 参数形状是 `[1, 2]`,这意味着你正在尝试为两个类别中的一个分配不同的权重。你需要将 `weight` 参数的形状更改为 `[2]`,并确保每个类别都有一个相应的权重值。
相关问题
RuntimeError: weight tensor should be defined either for all or no classes
回答: RuntimeError: weight tensor should be defined either for all or no classes是由于在计算损失函数时,权重张量应该对所有类别进行定义,要么对所有类别进行定义,要么对没有类别进行定义。\[1\]解决办法是,如果是多卡训练,可以采用"SyncBN"方法;如果是单卡训练,可以将type修改为'BN'。另外,还可以检查损失函数的输入和目标张量的维度是否一致,以及检查网络结构中是否有不支持自动混合精度训练的算子,导致出现nan值,最终导致计算loss时报错。\[2\]\[3\]
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shape mismatch: value tensor of shape [3, 1] cannot be broadcast to indexing result of shape [3]
This error occurs when there is a mismatch between the shape of the value tensor and the shape of the indexing result in a TensorFlow operation.
In this specific case, the error message is saying that a value tensor with shape [3, 1] (3 rows and 1 column) cannot be broadcast to an indexing result with shape [3] (3 elements).
Broadcasting is a technique used in TensorFlow to match the shapes of tensors when performing operations. However, in this case, the shapes cannot be broadcasted because they are not compatible.
To fix this error, you need to ensure that the shape of the value tensor matches the shape of the indexing result. One way to do this is to reshape the value tensor to have the same shape as the indexing result. For example, you could reshape the [3, 1] tensor to [3] by using the `tf.squeeze()` function:
```
value_tensor = tf.squeeze(value_tensor)
```
Alternatively, you could adjust the indexing operation to match the shape of the value tensor. For example, you could use an indexing operation that returns a tensor with shape [3, 1], such as:
```
result = tensor[indexes, tf.newaxis]
```
where `tf.newaxis` adds an extra dimension to the tensor, resulting in a shape of [3, 1].