TTNNOp - tt-mlir documentation

`ttnn.leaky_relu` (tt::ttnn::LeakyReluOp)

Eltwise leaky relu operation.

The Leaky ReLU (Rectified Linear Unit) operation computes an element-wise activation function over its input tensor. It is defined as:

y = x if x > 0 y = parameter * x if x <= 0

where parameter is a small, user-defined constant that determines the slope for negative inputs.

Attributes:

parameter (float): The slope for negative values.

Inputs:

input (Tensor): The input tensor to be activated.

Outputs:

output (Tensor): The tensor after applying the Leaky ReLU activation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`parameter`	::mlir::FloatAttr	32-bit float attribute

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.abs` (tt::ttnn::AbsOp)

Eltwise absolute.

Eltwise absolute operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.add` (tt::ttnn::AddOp)

Eltwise add.

Eltwise add operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.all_gather` (tt::ttnn::AllGatherOp)

All gather op.

Tensor All Gather operation

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`dim`	::mlir::IntegerAttr	32-bit signed integer attribute
`num_links`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.alloc` (tt::ttnn::AllocOp)

Alloc op.

Tensor Alloc operation

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`address`	::mlir::IntegerAttr	64-bit signless integer attribute
`size`	::mlir::IntegerAttr	64-bit signless integer attribute
`buffer_type`	::mlir::tt::ttnn::BufferTypeAttr	TTNN Buffer Type {{% markdown %}}Enum cases: * dram (`DRAM`) * l1 (`L1`) * system_memory (`SystemMemory`) * l1_small (`L1Small`) * trace (`Trace`){{% /markdown %}}

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.cbrt` (tt::ttnn::CbrtOp)

Eltwise cubic root.

Eltwise cubic root operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.ceil` (tt::ttnn::CeilOp)

Eltwise ceil.

Eltwise ceil operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.clamp` (tt::ttnn::ClampOp)

Clamp op.

Clamp tensor values to a specified range.

Example: min: 2.000000+00 input: [[0, 1, 2, 3, 4, 5, 6, 7]] max: 5.000000+00

"ttnn.clamp"(%arg0) <{max = 2.000000e+00 : f32, min = 5.000000e+00 : f32}> -> %out = [[2, 2, 2, 3, 4, 5, 5, 5]]

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`min`	::mlir::FloatAttr	32-bit float attribute
`max`	::mlir::FloatAttr	32-bit float attribute

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`result`	variadic of ranked tensor of any type values

`ttnn.concat` (tt::ttnn::ConcatOp)

Concat op.

Concat tensors along a given dimension.

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`dim`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`output`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.conv2d` (tt::ttnn::Conv2dOp)

Conv2d operation.

Applies a 2D convolution over an input image composed of several input planes.

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`in_channels`	::mlir::IntegerAttr	32-bit signless integer attribute
`out_channels`	::mlir::IntegerAttr	32-bit signless integer attribute
`batch_size`	::mlir::IntegerAttr	32-bit signless integer attribute
`input_height`	::mlir::IntegerAttr	32-bit signless integer attribute
`input_width`	::mlir::IntegerAttr	32-bit signless integer attribute
`kernel_height`	::mlir::IntegerAttr	32-bit signless integer attribute
`kernel_width`	::mlir::IntegerAttr	32-bit signless integer attribute
`stride_height`	::mlir::IntegerAttr	32-bit signless integer attribute
`stride_width`	::mlir::IntegerAttr	32-bit signless integer attribute
`padding_height`	::mlir::IntegerAttr	32-bit signless integer attribute
`padding_width`	::mlir::IntegerAttr	32-bit signless integer attribute
`dilation_height`	::mlir::IntegerAttr	32-bit signless integer attribute
`dilation_width`	::mlir::IntegerAttr	32-bit signless integer attribute
`groups`	::mlir::IntegerAttr	32-bit signless integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values
`weight`	ranked tensor of any type values
`bias`	ranked tensor of any type values
`output`	ranked tensor of any type values
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.cos` (tt::ttnn::CosOp)

Eltwise cosine.

Eltwise cosine operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.deallocate` (tt::ttnn::DeallocateOp)

Deallocate op.

Tensor Deallocate operation

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`force`	::mlir::BoolAttr	bool attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

`ttnn.div` (tt::ttnn::DivOp)

Eltwise divide.

Eltwise divide operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.embedding` (tt::ttnn::EmbeddingOp)

Embedding op.

Embedding operation.

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`input`	ranked tensor of any type values
`output`	ranked tensor of any type values
`weight`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.empty` (tt::ttnn::EmptyOp)

Empty op.

Tensor empty operation

Interfaces: NoMemoryEffect (MemoryEffectOpInterface), TTNN_OpModelInterface

Effects: MemoryEffects::Effect{}

Attributes:

Attribute	MLIR Type	Description
`shape`	::mlir::tt::ttnn::ShapeAttr	TTNN Shape attribute {{% markdown %}} TTNN shape attribute {{% /markdown %}}
`dtype`	::mlir::tt::DataTypeAttr	TT DataTypes {{% markdown %}}Enum cases: * f32 (`Float32`) * f16 (`Float16`) * bf16 (`BFloat16`) * bfp_f8 (`BFP_Float8`) * bfp_bf8 (`BFP_BFloat8`) * bfp_f4 (`BFP_Float4`) * bfp_bf4 (`BFP_BFloat4`) * bfp_f2 (`BFP_Float2`) * bfp_bf2 (`BFP_BFloat2`) * u32 (`UInt32`) * u16 (`UInt16`) * u8 (`UInt8`){{% /markdown %}}
`layout`	::mlir::tt::ttnn::LayoutAttr	TTNN Layout {{% markdown %}}Enum cases: * row_major (`RowMajor`) * tile (`Tile`) * invalid (`Invalid`){{% /markdown %}}
`memory_config`	::mlir::tt::ttnn::MemoryConfigAttr	TTNN MemoryConfig attribute {{% markdown %}} TTNN memory config attribute {{% /markdown %}}

Operands:

Operand	Description
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.eq` (tt::ttnn::EqualOp)

Eltwise equal to.

Eltwise equal to operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.exp` (tt::ttnn::ExpOp)

Eltwise exponential.

Eltwise exponential operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.expm1` (tt::ttnn::Expm1Op)

Eltwise unary op.

Performs element-wise exponential minus one operation on operand tensor and stores the result in the output tensor.

Example: %a: [[0, 1], [0, 0]] "ttnn.exmp1"(%a, %out) -> %out: [[0, 1.71828], [0, 0]]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.floor` (tt::ttnn::FloorOp)

Eltwise floor op.

Eltwise floor operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.from_device` (tt::ttnn::FromDeviceOp)

FromDevice op.

This op retrieves the input tensor from the given device.

Interfaces: TTNN_OpModelInterface

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.full` (tt::ttnn::FullOp)

Full op.

Tensor full operation

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`fillValue`	::mlir::FloatAttr	32-bit float attribute

Operands:

Operand	Description
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.gelu` (tt::ttnn::GeluOp)

Eltwise GELU.

Eltwise GELU operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.get_device` (tt::ttnn::GetDeviceOp)

Get Device op.

This op returns the current runtime device.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`mesh_shape`	::mlir::tt::ttnn::MeshShapeAttr	TTNN Mesh Shape {{% markdown %}} TTNN mesh shape {{% /markdown %}}

Results:

Result	Description
`device`	TT device

`ttnn.ge` (tt::ttnn::GreaterEqualOp)

Eltwise greater than or equal to.

Eltwise greater than or equal to operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.gt` (tt::ttnn::GreaterThanOp)

Eltwise greater than.

Eltwise greater than operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.isfinite` (tt::ttnn::IsFiniteOp)

Eltwise isfinite op.

Eltwise isfinite operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.le` (tt::ttnn::LessEqualOp)

Eltwise less than or equal to.

Eltwise less than or equal to operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.lt` (tt::ttnn::LessThanOp)

Eltwise less than.

Eltwise less than operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.log1p` (tt::ttnn::Log1pOp)

Eltwise log1p operation.

Performs element-wise logarithm plus one operation on operand tensor and puts the result in the output tensor.

Example: %a: [0.0, -0.999, 7.0, 6.38905621, 15.0] "ttnn.logp1"(%a, %out) -> %out: [0.0, -6.90776825, 2.07944155, 2.0, 2.77258873]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.log` (tt::ttnn::LogOp)

Eltwise logarithm.

Eltwise logarithm operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.logical_and` (tt::ttnn::LogicalAndOp)

Eltwise logical and.

Eltwise logical and operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.logical_not` (tt::ttnn::LogicalNotOp)

Eltwise logical not op.

Eltwise logical not operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.logical_or` (tt::ttnn::LogicalOrOp)

Eltwise logical or.

Eltwise logical or operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.logical_xor` (tt::ttnn::LogicalXorOp)

Eltwise logical xor.

Eltwise logical xor operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.matmul` (tt::ttnn::MatmulOp)

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`a`	ranked tensor of any type values
`b`	ranked tensor of any type values
`output`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.max` (tt::ttnn::MaxOp)

Max reduction op.

Max reduction op.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`keep_dim`	::mlir::BoolAttr	bool attribute
`dim_arg`	::mlir::ArrayAttr	32-bit integer array attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.max_pool2d` (tt::ttnn::MaxPool2dOp)

Applies a 2D max pooling over an input signal composed of several input planes.

Applies a 2D max pooling over an input signal composed of several input planes.

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`batch_size`	::mlir::IntegerAttr	32-bit signed integer attribute
`input_height`	::mlir::IntegerAttr	32-bit signed integer attribute
`input_width`	::mlir::IntegerAttr	32-bit signed integer attribute
`channels`	::mlir::IntegerAttr	32-bit signed integer attribute
`kernel_height`	::mlir::IntegerAttr	32-bit signed integer attribute
`kernel_width`	::mlir::IntegerAttr	32-bit signed integer attribute
`stride_height`	::mlir::IntegerAttr	32-bit signed integer attribute
`stride_width`	::mlir::IntegerAttr	32-bit signed integer attribute
`dilation_height`	::mlir::IntegerAttr	32-bit signed integer attribute
`dilation_width`	::mlir::IntegerAttr	32-bit signed integer attribute
`ceil_mode`	::mlir::BoolAttr	bool attribute
`padding_height`	::mlir::IntegerAttr	32-bit signed integer attribute
`padding_width`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values
`output`	ranked tensor of any type values
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.maximum` (tt::ttnn::MaximumOp)

Eltwise maximum OP.

Calculates maximum of input tensors' values element-wise and stores result in output tensor.

Example: %lhs: [[3, 2, 7], [1, 4, 4]] %rhs: [[1, 4, 2], [1, 2, 3]] "ttnn.maximum"(%lhs, %rhs, %out) -> %out: [[3, 4, 7], [1, 4, 4]]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.mean` (tt::ttnn::MeanOp)

Mean reduction op.

Mean reduction op.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`keep_dim`	::mlir::BoolAttr	bool attribute
`dim_arg`	::mlir::ArrayAttr	32-bit integer array attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.minimum` (tt::ttnn::MinimumOp)

Eltwise minimum OP.

Calculates minimum of input tensors' values element-wise and stores result in output tensor.

Example: %lhs: [[3, 2, 7], [1, 4, 4]] %rhs: [[1, 4, 2], [1, 2, 3]] "ttnn.minimum"(%lhs, %rhs, %out) -> %out: [[1, 2, 2], [1, 2, 3]]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.multiply` (tt::ttnn::MultiplyOp)

Eltwise multiply.

Eltwise multiply operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.neg` (tt::ttnn::NegOp)

Eltwise negate.

Eltwise negate operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.ne` (tt::ttnn::NotEqualOp)

Eltwise not equal to.

Eltwise not equal to operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.reciprocal` (tt::ttnn::ReciprocalOp)

Eltwise reciprocal.

Eltwise reciprocal operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.reduce_scatter` (tt::ttnn::ReduceScatterOp)

Reduce scatter op.

Tensor Reduce Scatter operation

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`scatter_split_dim`	::mlir::IntegerAttr	32-bit signed integer attribute
`math_op`	::mlir::IntegerAttr	TTNN Reduce Operation Type {{% markdown %}}Enum cases: * sum (`Sum`) * mean (`Mean`) * max (`Max`) * min (`Min`) * std (`Std`) * var (`Var`){{% /markdown %}}
`num_links`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.relu` (tt::ttnn::ReluOp)

Eltwise ReLU.

Eltwise ReLU operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, OpModel, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.remainder` (tt::ttnn::RemainderOp)

Eltwise remainder.

Performs element-wise remainder of dividend lhs and divisor rhs tensors and produces a result tensor.

Example:

// %lhs: [17, -17, 17, -17] // %rhs: [3, 3, -3, -3] %result = "ttnn.remainder"(%lhs, %rhs) : (tensor<4xi64>, tensor<4xi64>) -> tensor<4xi64> // %result: [2, -2, 2, -2]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.reshape` (tt::ttnn::ReshapeOp)

Reshape op.

Reshape tensor.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`shape`	::mlir::ArrayAttr	32-bit integer array attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.rsqrt` (tt::ttnn::RsqrtOp)

Eltwise rsqrt.

Eltwise rsqrt operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.sigmoid` (tt::ttnn::SigmoidOp)

Eltwise sigmoid.

Eltwise sigmoid operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.sign` (tt::ttnn::SignOp)

Eltwise sign operation.

Returns the sign of the operand element-wise and produces a result tensor.

Example: %a: [[3, -2, 0], [1, -4, 4]] "ttnn.sign"(%a, %out) -> %out: [[1, -1, 0], [1, -1, 1]]

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.sin` (tt::ttnn::SinOp)

Eltwise sine.

Eltwise sine operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.slice` (tt::ttnn::SliceOp)

Slice op.

Extract a portion of a tensor based on the specified start (begins), stop (ends), and step indices for each dimension.

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`begins`	::mlir::ArrayAttr	32-bit integer array attribute
`ends`	::mlir::ArrayAttr	32-bit integer array attribute
`step`	::mlir::ArrayAttr	32-bit integer array attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values
`output`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.softmax` (tt::ttnn::SoftmaxOp)

Softmax op.

Softmax operation.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`dimension`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.sqrt` (tt::ttnn::SqrtOp)

Eltwise sqrt.

Eltwise sqrt operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.subtract` (tt::ttnn::SubtractOp)

Eltwise subtract.

Eltwise subtract operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values

`ttnn.sum` (tt::ttnn::SumOp)

Sum reduction op.

Sum reduction op.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`keep_dim`	::mlir::BoolAttr	bool attribute
`dim_arg`	::mlir::ArrayAttr	32-bit integer array attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.to_device` (tt::ttnn::ToDeviceOp)

ToDevice op.

This op sends the input tensor to the given device with the given memory config.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`memory_config`	::mlir::tt::ttnn::MemoryConfigAttr	TTNN MemoryConfig attribute {{% markdown %}} TTNN memory config attribute {{% /markdown %}}

Operands:

Operand	Description
`input`	ranked tensor of any type values
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.to_layout` (tt::ttnn::ToLayoutOp)

ToLayout op.

This op wraps all layout information gathered from ttir.toLayout. It is used/updated by the optimizer to perform optimizations, and later broken down into specific memory/layout operations (toDevice, toMemoryConfig etc.). Currently in the TTNN backend, we use this op solely for tilize/untilize, therefore marking all other attrs as optional. Once ttnn::to_layout supports other attrs, we can remove the optional tag.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`layout`	::mlir::tt::ttnn::LayoutAttr	TTNN Layout {{% markdown %}}Enum cases: * row_major (`RowMajor`) * tile (`Tile`) * invalid (`Invalid`){{% /markdown %}}
`dtype`	::mlir::tt::DataTypeAttr	TT DataTypes {{% markdown %}}Enum cases: * f32 (`Float32`) * f16 (`Float16`) * bf16 (`BFloat16`) * bfp_f8 (`BFP_Float8`) * bfp_bf8 (`BFP_BFloat8`) * bfp_f4 (`BFP_Float4`) * bfp_bf4 (`BFP_BFloat4`) * bfp_f2 (`BFP_Float2`) * bfp_bf2 (`BFP_BFloat2`) * u32 (`UInt32`) * u16 (`UInt16`) * u8 (`UInt8`){{% /markdown %}}
`memory_config`	::mlir::tt::ttnn::MemoryConfigAttr	TTNN MemoryConfig attribute {{% markdown %}} TTNN memory config attribute {{% /markdown %}}

Operands:

Operand	Description
`input`	ranked tensor of any type values
`device`	TT device

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.to_memory_config` (tt::ttnn::ToMemoryConfigOp)

ToMemoryConfig op.

This op converts the memory config of the input tensor based on the given memory config. It handles:

Dram to L1
L1 to Dram
Interleaved to sharded
Sharded to interleaved
Sharded to sharded (reshard)

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`memory_config`	::mlir::tt::ttnn::MemoryConfigAttr	TTNN MemoryConfig attribute {{% markdown %}} TTNN memory config attribute {{% /markdown %}}

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.transpose` (tt::ttnn::TransposeOp)

Transpose op.

Transpose tensor along two given dimensions.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`dim0`	::mlir::IntegerAttr	32-bit signed integer attribute
`dim1`	::mlir::IntegerAttr	32-bit signed integer attribute

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.typecast` (tt::ttnn::TypecastOp)

Typecast op.

This op converts the data type of the input tensor based on the given data type. It handles:

conversions of data types.

Interfaces: TTNN_OpModelInterface

Attributes:

Attribute	MLIR Type	Description
`dtype`	::mlir::tt::DataTypeAttr	TT DataTypes {{% markdown %}}Enum cases: * f32 (`Float32`) * f16 (`Float16`) * bf16 (`BFloat16`) * bfp_f8 (`BFP_Float8`) * bfp_bf8 (`BFP_BFloat8`) * bfp_f4 (`BFP_Float4`) * bfp_bf4 (`BFP_BFloat4`) * bfp_f2 (`BFP_Float2`) * bfp_bf2 (`BFP_BFloat2`) * u32 (`UInt32`) * u16 (`UInt16`) * u8 (`UInt8`){{% /markdown %}}

Operands:

Operand	Description
`input`	ranked tensor of any type values

Results:

Result	Description
`result`	ranked tensor of any type values

`ttnn.where` (tt::ttnn::WhereOp)

Eltwise where.

Eltwise where operation.

Traits: AttrSizedOperandSegments

Interfaces: DestinationStyleOpInterface, TTNN_OpModelInterface

Operands:

Operand	Description
`inputs`	variadic of ranked tensor of any type values
`outputs`	variadic of ranked tensor of any type values

Results:

Result	Description
`results`	variadic of ranked tensor of any type values