# tensorplay.distributed.device_mesh API

Source: https://www.tensorplay.cn/docs/api/tensorplay.distributed.device_mesh.html

## Functions 1

[#](#api-tensorplay.distributed.device_mesh.init_device_mesh)

### init_device_mesh

function[Full reference ↗](/docs/generated/tensorplay.distributed.device_mesh.init_device_mesh.html)

```python
tensorplay.distributed.device_mesh.init_device_mesh(device_type: str, mesh_shape: tuple[int, ...], *, mesh_dim_names: tuple[str, ...] | None = None, backend_override=None) → DeviceMesh
```

This creates a DeviceMesh with an n-dimensional array layout, where n
is the length of mesh_shape. If mesh_dim_names is provided, each
dimension is labeled as mesh_dim_names[i].

> **Note**
>
> Follows SPMD: ensure mesh_shape is identical across all ranks.

Example:

```
>>> mesh_1d = init_device_mesh("cuda", mesh_shape=(8,))
>>> mesh_2d = init_device_mesh("cuda", mesh_shape=(2, 8),
...                             mesh_dim_names=("dp", "tp"))
```

## Classes 1

[#](#api-tensorplay.distributed.device_mesh.DeviceMesh)

### DeviceMesh

class[Full reference ↗](/docs/generated/tensorplay.distributed.device_mesh.DeviceMesh.html)

```python
class tensorplay.distributed.device_mesh.DeviceMesh(device_type: str, mesh=None, *, mesh_dim_names=None, _dim_group_names=None, _rank_map=None, _sizes=None, _strides=None, _root_mesh=None, _backend_override=None, _axis_root_dims=None)
```

The mesh is an n-d array whose values are global ranks. Process groups
are created per mesh dimension so collectives can run on each dimension
independently.

Example:

```
>>> from tensorplay.distributed.device_mesh import init_device_mesh
>>> mesh = init_device_mesh("cuda", mesh_shape=(2, 4),
...                         mesh_dim_names=("dp", "tp"))
```

```python
classmethod from_group(group, device_type=None, mesh=None, mesh_dim_names=None) → DeviceMesh
```

Construct a DeviceMesh from one or more existing process groups.

```python
get_coordinate() → tuple[int, ...] | None
```

Returns this rank’s coordinate in the mesh, or None if absent.