softmax_loss

allennlp.modules.softmax_loss

[SOURCE]

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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. Does not add a padding ID into the vocabulary, and input targets to forward should not include a padding ID.

forward

class SoftmaxLoss(torch.nn.Module):
 | ...
 | def forward(
 |     self,
 |     embeddings: torch.Tensor,
 |     targets: torch.Tensor
 | ) -> torch.Tensor

Parameters

• embeddings : torch.Tensor
  A tensor of shape (sequence_length, embedding_dim)
• targets : torch.Tensor
  A tensor of shape (batch_size, )

Returns

• loss : torch.FloatTensor
  A scalar loss to be optimized.