Computes sums, means or maxes of `bags`

of embeddings, without instantiating the
intermediate embeddings.

## Usage

```
nnf_embedding_bag(
input,
weight,
offsets = NULL,
max_norm = NULL,
norm_type = 2,
scale_grad_by_freq = FALSE,
mode = "mean",
sparse = FALSE,
per_sample_weights = NULL,
include_last_offset = FALSE,
padding_idx = NULL
)
```

## Arguments

- input
(LongTensor) Tensor containing bags of indices into the embedding matrix

- weight
(Tensor) The embedding matrix with number of rows equal to the maximum possible index + 1, and number of columns equal to the embedding size

- offsets
(LongTensor, optional) Only used when

`input`

is 1D.`offsets`

determines the starting index position of each bag (sequence) in`input`

.- max_norm
(float, optional) If given, each embedding vector with norm larger than

`max_norm`

is renormalized to have norm`max_norm`

. Note: this will modify`weight`

in-place.- norm_type
(float, optional) The

`p`

in the`p`

-norm to compute for the`max_norm`

option. Default`2`

.- scale_grad_by_freq
(boolean, optional) if given, this will scale gradients by the inverse of frequency of the words in the mini-batch. Default

`FALSE`

. Note: this option is not supported when`mode="max"`

.- mode
(string, optional)

`"sum"`

,`"mean"`

or`"max"`

. Specifies the way to reduce the bag. Default: 'mean'- sparse
(bool, optional) if

`TRUE`

, gradient w.r.t.`weight`

will be a sparse tensor. See Notes under`nn_embedding`

for more details regarding sparse gradients. Note: this option is not supported when`mode="max"`

.- per_sample_weights
(Tensor, optional) a tensor of float / double weights, or NULL to indicate all weights should be taken to be 1. If specified,

`per_sample_weights`

must have exactly the same shape as input and is treated as having the same`offsets`

, if those are not`NULL`

.- include_last_offset
(bool, optional) if

`TRUE`

, the size of offsets is equal to the number of bags + 1.- padding_idx
(int, optional) If given, pads the output with the embedding vector at

`padding_idx`

(initialized to zeros) whenever it encounters the index.