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embedding_bag

torch.nn.functional.embedding_bag

function embedding_bag<S extends readonly [number, number]>(input: Tensor<S>, weight: Tensor, options?: EmbeddingBagFunctionalOptions): Tensor

function embedding_bag(input: Tensor, weight: Tensor, offsets: Tensor | undefined, max_norm: number | undefined, norm_type: number, scale_grad_by_freq: boolean, mode: 'sum' | 'mean' | 'max', sparse: boolean, per_sample_weights: Tensor | undefined, include_last_offset: boolean, padding_idx: number | undefined, options?: EmbeddingBagFunctionalOptions): Tensor

Compute sums, means, or maxes of bags of embeddings.

NOTE: Currently only 2D input is supported, where each row is a bag. 1D input with offsets is not yet implemented.

Parameters

inputTensor<S>: Tensor of indices (must be 2D: [num_bags, bag_size])
weightTensor: Embedding weight matrix of shape (num_embeddings, embedding_dim)
optionsEmbeddingBagFunctionalOptionsoptional

Returns

Tensor

See Also

PyTorch torch.nn.functional.embedding_bag

EmbeddingBagFunctionalOptions