Embeddings Objects — embeddings • embedplyr

An embeddings object is a numeric matrix with fast indexing by rownames (generally tokens).

Usage

embeddings(data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL)

as.embeddings(x, ...)

# Default S3 method
as.embeddings(x, ..., rowname_repair = TRUE, rebuild_token_index = TRUE)

# S3 method for class 'data.frame'
as.embeddings(x, id_col = NULL, ..., rowname_repair = TRUE)

is.embeddings(x, ...)

Arguments

data: an optional data vector (including a list or expression vector). Non-atomic classed R objects are coerced by as.vector and all attributes discarded.
nrow: the desired number of rows.
ncol: the desired number of columns.
byrow: logical. If FALSE (the default) the matrix is filled by columns, otherwise the matrix is filled by rows.
dimnames: a dimnames attribute for the matrix: NULL or a list of length 2 giving the row and column names respectively. An empty list is treated as NULL, and a list of length one as row names. The list can be named, and the list names will be used as names for the dimensions.
x: A data frame to be converted into embeddings.
...: Additional arguments passed to or from other methods.
rowname_repair: logical. If TRUE (the default), check that unique rownames are provided, and name rows "doc_1", "doc_2", etc. if not.
rebuild_token_index: logical. If TRUE, the hash table index will be rebuilt even when x is an embeddings object.
id_col: Optional name of a column to take row names from.

Details

Fast row indexing is implemented using hash tables in native R environments. The "token_index" attribute of an embeddings object stores the environment that maps rownames to their corresponding indices.

If dimnames is not supplied, embeddings will automatically name rows doc_1, doc_2, etc., and columns dim_1, dim_2, etc.

Examples

random_mat <- matrix(
  sample(1:10, 20, replace = TRUE),
  nrow = 2,
  dimnames = list(c("happy", "sad"))
  )
random_embeddings <- as.embeddings(random_mat)
is.embeddings(random_embeddings[,2:5])
#> [1] TRUE

tibble::as_tibble(random_embeddings, rownames = "token")
#> # A tibble: 2 × 11
#>   token dim_1 dim_2 dim_3 dim_4 dim_5 dim_6 dim_7 dim_8 dim_9 dim_10
#>   <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int>  <int>
#> 1 happy     7     6     6     5     8     7     5     6     2      9
#> 2 sad       5     4     9     5     2     5     2     4     3      6