如何求出张量沿维数的最大值？
如何求出张量沿维数的最大值？
提问于 2022-09-30 00:10:26
我有一个三维张量，我想取最大值沿第0维在利比里亚火炬。
我知道如何用Python (PyTorch)来完成这个任务，但在LibTorch中却遇到了困难。
在LibTorch中，我的代码是
auto target_q_T = torch::rand({5, 10, 1});
auto max_q = torch::max({target_q_T}, 0);
std::cout << max_q;它会返回这么长的重复错误。
note: candidate: ‘template<class _Traits> std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, _Traits>&, const char*)’
611 | operator<<(basic_ostream<char, _Traits>& __out, const char* __s)
| ^~~~~~~~
/usr/include/c++/11/ostream:611:5: note: template argument deduction/substitution failed:
/home/iii/tor/m_gym/multiv_normal.cpp:432:18: note: cannot convert ‘max_q’ (type ‘std::tuple<at::Tensor, at::Tensor>’) to type ‘const char*’
432 | std::cout << max_q;
| ^~~~~
In file included from /usr/include/c++/11/istream:39,
from /usr/include/c++/11/sstream:38,
from /home/iii/tor/m_gym/libtorch/include/c10/macros/Macros.h:246,
from /home/iii/tor/m_gym/libtorch/include/c10/core/DeviceType.h:8,
from /home/iii/tor/m_gym/libtorch/include/c10/core/Device.h:3,
from /home/iii/tor/m_gym/libtorch/include/ATen/core/TensorBody.h:11,
from /home/iii/tor/m_gym/libtorch/include/ATen/core/Tensor.h:3,
from /home/iii/tor/m_gym/libtorch/include/ATen/Tensor.h:3,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/autograd/function_hook.h:3,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/autograd/cpp_hook.h:2,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/autograd/variable.h:6,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/autograd/autograd.h:3,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/api/include/torch/autograd.h:3,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/api/include/torch/all.h:7,
from /home/iii/tor/m_gym/libtorch/include/torch/csrc/api/include/torch/torch.h:3,
from /home/iii/tor/m_gym/multiv_normal.cpp:2:
/usr/include/c++/11/ostream:624:5: note: candidate: ‘template<class _Traits> std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, _Traits>&, const signed char*)’
624 | operator<<(basic_ostream<char, _Traits>& __out, const signed char* __s)
| ^~~~~~~~这就是它在Python中的工作方式。
target_q_np = torch.rand(5, 10, 1)
max_q = torch.max(target_q_np, 0)
max_q
torch.return_types.max(
values=tensor([[0.8517],
[0.7526],
[0.6546],
[0.9913],
[0.8521],
[0.9757],
[0.9080],
[0.9376],
[0.9901],
[0.7445]]),
indices=tensor([[4],
[2],
[3],
[4],
[1],
[0],
[2],
[4],
[4],
[4]]))回答 2
Stack Overflow用户
回答已采纳
发布于 2022-10-01 03:48:06
如果您读取编译器错误，它基本上告诉您您正在尝试打印两个张量的元组。这是因为C++代码的工作方式与python代码完全一样，并返回最大值及其各自的索引(您的python代码正是这样打印的)。您需要性病获取从元组中提取张量：
auto target_q_T = torch::rand({5, 10, 1});
auto max_q = torch::max({target_q_T}, 0);
std::cout << "max: " << std::get<0>(max_q)
<< "indices: " << std::get<1>(max_q)
<< std::endl;在C++17中，您还应该能够编写
auto [max_t, idx_t] = torch::max({target_q_T}, 0);
std::cout << ... ;Stack Overflow用户
发布于 2022-10-01 02:50:16
我从来没有发现max在LibTorch中的相同用法，就像在PyTorch中一样，所以我做了一个解决方案。
max在LibTorch中将从一个一维数组中获取最大值，因此我在索引数组上循环并连接结果。它实际上返回与torch.max(target_q_np，0)相同的内容。
我的解决方案在LibTorch (C++)。最大值数组以反向顺序返回，作为原始张量，因此我将其翻转。
auto target_q_T = torch::rand({5, 10, 1});
torch::Tensor zero_max;
for (int i=0; i<5; i++) {
zero_max = torch::cat({torch::max({target_q_T[i]}).unsqueeze(-1), zero_max}, 0);
}
zero_max = zero_max.flip(-1);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/73902752
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