Skip to main content

Mojo function

layer_norm_shape

layer_norm_shape[dtype: DType](input: TileTensor[dtype, input.LayoutType, input.origin, address_space=input.address_space, linear_idx_type=input.linear_idx_type, element_size=input.element_size], gamma: TileTensor[dtype, gamma.LayoutType, gamma.origin, address_space=gamma.address_space, linear_idx_type=gamma.linear_idx_type, element_size=gamma.element_size], beta: TileTensor[dtype, beta.LayoutType, beta.origin, address_space=beta.address_space, linear_idx_type=beta.linear_idx_type, element_size=beta.element_size], epsilon: Scalar[dtype]) -> IndexList[TileTensor[dtype, input.LayoutType, input.origin, address_space=input.address_space, linear_idx_type=input.linear_idx_type, element_size=input.element_size].rank]

Compute the output shape of a layer_norm operation.

Parameters:

  • dtype (DType): Type of the input tensors.

Args:

  • input (TileTensor): The input tensor.
  • gamma (TileTensor): The tensor for gamma coefficient.
  • beta (TileTensor): The tensor for beta coefficient.
  • epsilon (Scalar): The tensor for epsilon coefficient.

Returns:

IndexList: The output shape.

Was this page helpful?