r"""Applies lookup table for embedding. Args: inp: tensor with indices. weight: learnable weights which embeds from. padding_idx: should be set to None, not supported now. max_norm: should be set to None, not supported now. norm_type: should be set to Non
(
inp: Tensor,
weight: Tensor,
padding_idx: Optional[int] = None,
max_norm: Optional[float] = None,
norm_type: Optional[float] = None,
)
| 1667 | |
| 1668 | |
| 1669 | def embedding( |
| 1670 | inp: Tensor, |
| 1671 | weight: Tensor, |
| 1672 | padding_idx: Optional[int] = None, |
| 1673 | max_norm: Optional[float] = None, |
| 1674 | norm_type: Optional[float] = None, |
| 1675 | ): |
| 1676 | r"""Applies lookup table for embedding. |
| 1677 | |
| 1678 | Args: |
| 1679 | inp: tensor with indices. |
| 1680 | weight: learnable weights which embeds from. |
| 1681 | padding_idx: should be set to None, not supported now. |
| 1682 | max_norm: should be set to None, not supported now. |
| 1683 | norm_type: should be set to None, not supported now. |
| 1684 | |
| 1685 | Refer to :class:`~.module.Embedding` for more information. |
| 1686 | """ |
| 1687 | if padding_idx is not None: |
| 1688 | raise ValueError("Not support padding_idx Now!") |
| 1689 | if max_norm is not None or norm_type is not None: |
| 1690 | raise ValueError("Not support weight normlization Now!") |
| 1691 | |
| 1692 | dest_shp = list(inp.shape) + [weight.shape[-1]] |
| 1693 | return weight[inp.reshape(-1)].reshape(dest_shp) |
| 1694 | |
| 1695 | |
| 1696 | def indexing_one_hot( |