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Python class

Sharded

`Sharded`

class max.experimental.sharding.Sharded(axis, even=True)

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Bases: Placement

Every device on this mesh axis holds a slice along axis.

Parameters:

axis (int) – The tensor axis along which data is split.
even (bool) – When True, per-shard cells of a dynamic axis parent stay connected via uniform parent // n. When False, scatter mints fresh per-shard cells so each rank can bind to a different extent.

`axis`

axis: int

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`even`

even: bool = True

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`global_dim()`

global_dim(cells)

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Sums per-shard cells along this mesh axis.

Parameters:: cells (Dim)
Return type:: Dim

`local_dim()`

local_dim(parent, mesh, mesh_axis, *, allow_symbolic_mint=True)

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Splits parent along mesh_axis into per-shard cells.

StaticDim parents use uneven divmod; SymbolicDim parents mint fresh per-shard cells; AlgebraicDim parents raise. Wrapper parents pass through verbatim. When allow_symbolic_mint is False, a bare SymbolicDim raises instead of minting.

Parameters:

parent (int | str | Dim | integer | TypedAttr)
mesh (DeviceMesh)
mesh_axis (int)
allow_symbolic_mint (bool)

Return type:

Dim

`localized_axis()`

localized_axis()

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Returns the tensor axis this Sharded localizes.

Return type:: int | None

`transition_to()`

transition_to(other)

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Sharded-to-Replicated is allgather; Sharded-to-Sharded is all-to-all.

Parameters:: other (Placement)
Return type:: Collective

Sharded​

axis​

even​

global_dim()​

local_dim()​

localized_axis()​

transition_to()​