我有一个Torch张量z，我想将一个转换矩阵mat应用于z，并使输出的大小与z完全相同。这是我正在运行的代码：
def trans(z):
print(z)
mat = transforms.Compose([transforms.ToPILImage(),transforms.RandomRotation(90),transforms.ToTensor()])
z = Variable(mat(z.cpu()).cuda())
z = nnf.interpolate(z, size=(28, 28), mode='linear', align_corners=False)
return z
z = trans(z)
但是，出现此错误：
RuntimeError Traceback (most recent call last)
<ipython-input-12-e2fc36889ba5> in <module>()
3 inputs,targs=next(iter(tst_loader))
4 recon, mean, var = vae.predict(model, inputs[img_idx])
----> 5 out = vae.generate(model, mean, var)
4 frames
/content/vae.py in generate(model, mean, var)
90 z = trans(z)
91 z = Variable(z.cpu().cuda())
---> 92 out = model.decode(z)
93 return out.data.cpu()
94
/content/vae.py in decode(self, z)
56
57 def decode(self, z):
---> 58 out = self.z_develop(z)
59 out = out.view(z.size(0), 64, self.z_dim, self.z_dim)
60 out = self.decoder(out)
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/linear.py in forward(self, input)
89
90 def forward(self, input: Tensor) -> Tensor:
---> 91 return F.linear(input, self.weight, self.bias)
92
93 def extra_repr(self) -> str:
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in linear(input, weight, bias)
1674 ret = torch.addmm(bias, input, weight.t())
1675 else:
-> 1676 output = input.matmul(weight.t())
1677 if bias is not None:
1678 output += bias
RuntimeError: mat1 dim 1 must match mat2 dim 0
如何成功应用此旋转变换mat并且这样做没有错误？
谢谢， 温尼
答案 0 :(得分：1)
问题是overflow:auto期望一个批处理维度，并且基于错误消息和[root] {
height: 100vh;
display: flex;
flex-direction: column;
}
[page] {
flex: 1;
display: flex;
flex-direction: column;
}
[content] {
flex: 1 0 0;
overflow: auto;
}
/* Sticky Header */
table {
position: relative;
}
th {
position: sticky;
top: 0;
background: black;
color: white;
}的成功应用，您的数据似乎没有一个维度。由于您的输入是空间输入（基于<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css" integrity="sha384-JcKb8q3iqJ61gNV9KGb8thSsNjpSL0n8PARn9HuZOnIxN0hoP+VmmDGMN5t9UJ0Z" crossorigin="anonymous">
<div root>
<div navbar>
<nav class="navbar navbar-expand-lg navbar-dark bg-dark"><a class="navbar-brand" href="#">Company</a><button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"><span class="navbar-toggler-icon"></span></button>
<div class="collapse navbar-collapse" id="navbarNav">
<ul class="navbar-nav mr-auto">
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar1</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar2</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar3</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar4</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar5</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar6</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar7</a></li>
<li class="nav-item"><a id="vehicles_navbar" class="nav-link" href="#">navbar8</a></li>
</ul>
</div>
</nav>
</div>
<div page>
<div header>
<h1>HEADER</h1>
</div>
<div content>
<div>
<table class="table">
<thead>
<tr>
<th scope="col">Column 1</th>
<th scope="col">Column 2</th>
<th scope="col">Column 3</th>
<th scope="col"> Column 4 </th>
<th scope="col">Column 5</th>
</tr>
</thead>
<tbody class="table_body">
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
<tr>
<td colspan="5">
<h3>Row</h3>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div footer>
<h2>Footer</h2>
</div>
</div>
</div>），您可以通过添加批处理尺寸并更改interpolate来解决此问题，因为对于空间输入，transforms是not implemented：
size=(28, 28)如果您希望mode仍然具有（C，H，W）的形状，则：
linear