setup({
sc <- testthat_spark_connection()
text_tbl <- testthat_tbl("test_text")
# These lines should set a pipeline that will ultimately create the columns needed for testing the annotator
assembler <- nlp_document_assembler(sc, input_col = "text", output_col = "document")
pipeline <- ml_pipeline(assembler)
test_data <- ml_fit_and_transform(pipeline, text_tbl)
assign("sc", sc, envir = parent.frame())
assign("pipeline", pipeline, envir = parent.frame())
assign("test_data", test_data, envir = parent.frame())
})
teardown({
spark_disconnect(sc)
rm(sc, envir = .GlobalEnv)
rm(pipeline, envir = .GlobalEnv)
rm(test_data, envir = .GlobalEnv)
})
test_that("nlp_roberta_sentence_embeddings pretrained", {
model <- nlp_roberta_sentence_embeddings_pretrained(sc, input_cols = c("document"), output_col = "roberta_sentence_embeddings")
transformed_data <- ml_transform(model, test_data)
expect_true("roberta_sentence_embeddings" %in% colnames(transformed_data))
expect_true(inherits(model, "nlp_roberta_sentence_embeddings"))
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.