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Mojo struct
ReduceRMSNormFusedResidualAdd
struct ReduceRMSNormFusedResidualAdd
Registers the mo.composite.rms_norm_fused_residual_add graph op with the graph compiler.
Implemented traits
Methods
execute
static def execute[dtype: DType, rank: Int, target: StringSlice[ImmStaticOrigin], multiply_before_cast: Bool = True](output: ManagedTensorSlice[IOSpec[_, _].Output, static_spec=output.static_spec], residual_output: ManagedTensorSlice[IOSpec[_, _].Output, static_spec=residual_output.static_spec], input: ManagedTensorSlice[IOSpec[_, _].FusedInput, static_spec=input.static_spec], residual_input: ManagedTensorSlice[IOSpec[_, _].FusedInput, static_spec=residual_input.static_spec], gamma1: ManagedTensorSlice[IOSpec[_, _].Input, static_spec=gamma1.static_spec], gamma2: ManagedTensorSlice[IOSpec[_, _].Input, static_spec=gamma2.static_spec], epsilon1: Float32, epsilon2: Float32, weight_offset1: Scalar[dtype], weight_offset2: Scalar[dtype], ctx: DeviceContext)
Executes the mo.composite.rms_norm_fused_residual_add graph op.
Parameters:
- dtype (
DType): Element type of the input and output tensors. - rank (
Int): Tensor rank of the input and output tensors. - target (
StringSlice[ImmStaticOrigin]): Compilation target string. - multiply_before_cast (
Bool): See the graph op signature.
Args:
- output (
ManagedTensorSlice[IOSpec[_, _].Output, static_spec=output.static_spec]): Output tensor receiving the result. - residual_output (
ManagedTensorSlice[IOSpec[_, _].Output, static_spec=residual_output.static_spec]): See the graph op signature. - input (
ManagedTensorSlice[IOSpec[_, _].FusedInput, static_spec=input.static_spec]): Input tensor to reduce. - residual_input (
ManagedTensorSlice[IOSpec[_, _].FusedInput, static_spec=residual_input.static_spec]): Residual tensor added to the normalized input. - gamma1 (
ManagedTensorSlice[IOSpec[_, _].Input, static_spec=gamma1.static_spec]): Scale weights for the first normalization. - gamma2 (
ManagedTensorSlice[IOSpec[_, _].Input, static_spec=gamma2.static_spec]): Scale weights for the second normalization. - epsilon1 (
Float32): Stability constant for the first normalization. - epsilon2 (
Float32): Stability constant for the second normalization. - weight_offset1 (
Scalar[dtype]): Scalar offset for the first weight. - weight_offset2 (
Scalar[dtype]): Scalar offset for the second weight. - ctx (
DeviceContext): Device context used to enqueue the kernel.
Raises:
Error: If the operation parameters are invalid.
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