Struct melior::dialect::ods::bufferization::AllocTensorOperation

pub struct AllocTensorOperation<'c> { /* private fields */ }

An alloc_tensor operation. Allocate buffer for a tensor.

bufferization.alloc_tensor materializes an uninitialized tensor with a given shape (dynamic or static). It always bufferizes to a new buffer allocation of the given shape. The optional copy operand specifies the contents of the tensors. If no copy operand is specified, reading from the result of an alloc_tensor op yields an undefined value.

If copy is specified, no dynamic sizes should be passed, since they are the same as the dynamic sizes of the copy operand.

alloc_tensor is a helper op for bufferization. The operation is provided as an anchor that marks the beginning of a new tensor SSA use-def chain. It can be used to control in-place bufferization decisions during One-Shot Bufferize: The bufferized result of a bufferization.alloc_tensor does not alias with any other buffer, so it can be used to resolve read-after-write conflicts that would have been introduced by the in-place bufferization of another op.

The optional memory_space attribute specifies the memory space when bufferizing this op. The memory space is inferred from copy if specified. If neither copy nor memory_space is specified, the default memory space is used during bufferization.

The optional size_hint operand specifies the number of non-zero elements for sparse tensors. The value of size_hint should be not less than 1 and not larger than the linear size of the corresponding dense tensor type. If this requirement is not met, the behavior of the operator is undefined.

Both dense and sparse tensor types are supported. The result of a bufferization.alloc_tensor is a tensor value that can be used like any other tensor value. In practice, it is often used as the “out” operand of another op. Sparse tensor allocations should always be used in a local construction operation and never escape the function boundary directly.

Example:

%c = bufferization.alloc_tensor(%d1, %d2) : tensor<?x?xf32, #SparseMatrix>
%0 = linalg.matmul
  ins(%a, %b: tensor<?x?xf32, #SparseMatrix>, tensor<?x?xf32, #SparseMatrix>)
  outs(%c: tensor<?x?xf32, #SparseMatrix>) -> tensor<?x?xf32, #SparseMatrix>
return %0 : tensor<?x?xf32, #SparseMatrix>

%c = bufferization.alloc_tensor(%d1, %d2) size_hint = %noe
  : tensor<?x?xf32, #SparseMatrix>

Note: An alloc_tensor with a copy should also be expressed as an alloc_tensor without copy, followed by a copy_tensor.

Implementations

impl<'c> AllocTensorOperation<'c>

pub fn name() -> &'static str

Returns a name.

pub fn as_operation(&self) -> &Operation<'c>

Returns a generic operation.

pub fn builder( context: &'c Context, location: Location<'c> ) -> AllocTensorOperationBuilder<'c, Unset, Unset>

Creates a builder.

pub fn result(&self) -> Result<OperationResult<'c, '_>, Error>

pub fn dynamic_sizes( &self ) -> Result<impl Iterator<Item = Value<'c, '_>>, Error>

pub fn copy(&self) -> Result<Value<'c, '_>, Error>

pub fn size_hint(&self) -> Result<Value<'c, '_>, Error>

pub fn memory_space(&self) -> Result<Attribute<'c>, Error>

pub fn set_memory_space(&mut self, value: Attribute<'c>)

pub fn remove_memory_space(&mut self) -> Result<(), Error>

Trait Implementations

impl<'c> From<AllocTensorOperation<'c>> for Operation<'c>

fn from(operation: AllocTensorOperation<'c>) -> Self

Converts to this type from the input type.

impl<'c> TryFrom<Operation<'c>> for AllocTensorOperation<'c>

type Error = Error

The type returned in the event of a conversion error.

fn try_from(operation: Operation<'c>) -> Result<Self, Self::Error>

Performs the conversion.