Mojo function
layer_norm_shape
layer_norm_shape[dtype: DType, single_thread_blocking_override: Bool](input: TileTensor[dtype, LayoutType, origin, address_space=address_space, linear_idx_type=linear_idx_type, element_shape_types=element_shape_types], gamma: TileTensor[dtype, LayoutType, origin, address_space=address_space, linear_idx_type=linear_idx_type, element_shape_types=element_shape_types], beta: TileTensor[dtype, LayoutType, origin, address_space=address_space, linear_idx_type=linear_idx_type, element_shape_types=element_shape_types], epsilon: Scalar[dtype]) -> IndexList[TileTensor[dtype, LayoutType, origin, address_space=address_space, linear_idx_type=linear_idx_type, element_shape_types=element_shape_types].rank]
Compute the output shape of a layer_norm operation.
Parameters:
- dtype (
DType): Type of the input tensors. - single_thread_blocking_override (
Bool): If True, then the operation is run synchronously using a single thread.
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.
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