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# Transpose

The transpose operation permutes the dimensions of a tensor according to a **permutation** vector. For each output axis `i`, the value `permutation[i]` is the source axis taken from the input (so `output_dim[i] = input_dim[permutation[i]]`, and strides are permuted the same way).

On supported cuDNN versions, the graph lowers to the backend **transpose** operation (`CUDNN_BACKEND_OPERATION_TRANSPOSE_DESCRIPTOR`).

## Requirements

- Native backend transpose support requires **cuDNN 9.22.0** or newer. Older toolkits may report `GRAPH_NOT_SUPPORTED` for transpose nodes.

## C++ API

```cpp
std::shared_ptr<Tensor_attributes>
transpose(std::shared_ptr<Tensor_attributes> input, Transpose_attributes attributes);
```

`Transpose_attributes` provides:

```cpp
Transpose_attributes&
set_permutation(std::vector<int64_t> const& value);

Transpose_attributes&
set_name(std::string const& value);

Transpose_attributes&
set_compute_data_type(DataType_t value);  // optional; types usually follow the input
```

The permutation must have length equal to the input rank, contain each index `0 .. rank-1` exactly once, and describe where each **output** axis reads from in the **input**.

## Python API

- `pygraph.transpose(input, permutation, name="")`
  - **input**: source tensor.
  - **permutation**: list of ints, same semantics as C++.
  - **name**: optional node name.

## Example (C++)

```cpp
auto X = graph.tensor(/* ... */);  // e.g. dims {2, 4}, row-major strides
auto Y = graph.transpose(
    X,
    cudnn_frontend::graph::Transpose_attributes()
        .set_name("t")
        .set_permutation({1, 0}));  // dims become {4, 2}
Y->set_output(true);
```