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Python class

SymbolicDim

SymbolicDim

class max.graph.SymbolicDim(value)

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Bases: Dim

A symbolic tensor dimension.

Symbolic dimensions represent named dimensions in MO tensor types.

Symbolic dimensions don’t have a static value, but they allow a readable name to understand what’s going on in the model IR better, and they also allow users to hint to the compiler that two dimensions will have the same value, which can often allow important speedups.

In tensor type notation:

!mo.tensor<[batch, x, 10], si32]>

The first and second dimensions are named batch and x respectively.

Creating a SymbolicDim:

dim = SymbolicDim("name")

Using SymbolicDim in a TensorType:

tensor_type = TensorType(DType.bool, (SymbolicDim("batch"), SymbolicDim("x"), 10))

Converts valid input values to Dim.

Parameters:

name (str)

from_mlir()

static from_mlir(attr)

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Constructs a SymbolicDim from a kgen.ParamDeclRefAttr.

Parameters:

attr (TypedAttr) – The kgen.ParamDeclRefAttr to parse into a SymbolicDim.

Returns:

The SymbolicDim represented by the kgen.ParamDeclRefAttr.

Return type:

SymbolicDim

name

name: str

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The name of the dimension.

parameters

property parameters: Iterable[SymbolicDim]

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Lists the symbolic dimension names on which this dim depends.

to_mlir()

to_mlir()

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Creates an mlir.Attribute representing this dimension.

This is used internally when constructing tensor MLIR types.

Returns:

An mlir.Attribute in the context representing the dimension.

Return type:

ParamDeclRefAttr