mindsponge.cell

API Name	Description	Supported Platforms
`mindsponge.cell.Attention`	This is an implementation of multihead attention in the paper Attention is all you need.	`Ascend` `GPU`
`mindsponge.cell.GlobalAttention`	This is an implementation of global gated self attention in the paper Highly accurate protein structure prediction with AlphaFold.	`Ascend` `GPU`
`mindsponge.cell.InvariantPointAttention`	Invariant Point attention module.	`Ascend` `GPU`
`mindsponge.cell.MSAColumnAttention`	MSA column-wise gated self attention.	`Ascend` `GPU`
`mindsponge.cell.MSAColumnGlobalAttention`	MSA column global attention.	`Ascend` `GPU`
`mindsponge.cell.MSARowAttentionWithPairBias`	MSA row attention.	`Ascend` `GPU`
`mindsponge.cell.OuterProductMean`	Computing the correlation of the input tensor along its second dimension, the computed correlation could be used to update the correlation features(e.g.	`Ascend` `GPU`
`mindsponge.cell.Transition`	This is 2-layer MLP where the intermediate layer expands number of channels of the input by a factor(num_intermediate_factor).	`Ascend` `GPU`
`mindsponge.cell.TriangleAttention`	Triangle attention.	`Ascend` `GPU`
`mindsponge.cell.TriangleMultiplication`	Triangle multiplication layer.	`Ascend` `GPU`