softmax_loss
allennlp.modules.softmax_loss
SoftmaxLoss#
class SoftmaxLoss(torch.nn.Module):
| def __init__(self, num_words: int, embedding_dim: int) -> None
Given some embeddings and some targets, applies a linear layer to create logits over possible words and then returns the negative log likelihood.
forward#
class SoftmaxLoss(torch.nn.Module):
| ...
| def forward(
| self,
| embeddings: torch.Tensor,
| targets: torch.Tensor
| ) -> torch.Tensor
embeddings is size (n, embedding_dim) targets is (batch_size, ) with the correct class id Does not do any count normalization / divide by batch size