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")
sentdetect <- nlp_sentence_detector(sc, input_cols = c("document"), output_col = "sentence")
# TODO: put other annotators here as needed
pipeline <- ml_pipeline(assembler, sentdetect)
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)
})
# There are no "getter" methods in the RecursiveTokenizer class so this test will fail
# test_that("recursive_tokenizer param setting", {
# test_args <- list(
# input_cols = c("string1"),
# output_col = "string1",
# infixes = c("string1", "string2"),
# prefixes = c("string1", "string2"),
# suffixes = c("string1", "string2"),
# white_list = c("string1", "string2")
# )
#
# test_param_setting(sc, nlp_recursive_tokenizer, test_args)
# })
test_that("nlp_recursive_tokenizer spark_connection", {
test_annotator <- nlp_recursive_tokenizer(sc, input_cols = c("document"), output_col = "token")
fit_model <- ml_fit(test_annotator, test_data)
transformed_data <- ml_transform(fit_model, test_data)
expect_true("token" %in% colnames(transformed_data))
expect_true(inherits(test_annotator, "nlp_recursive_tokenizer"))
expect_true(inherits(fit_model, "nlp_recursive_tokenizer_model"))
})
test_that("nlp_recursive_tokenizer ml_pipeline", {
test_annotator <- nlp_recursive_tokenizer(pipeline, input_cols = c("document"), output_col = "token")
transformed_data <- ml_fit_and_transform(test_annotator, test_data)
expect_true("token" %in% colnames(transformed_data))
})
test_that("nlp_recursive_tokenizer tbl_spark", {
transformed_data <- nlp_recursive_tokenizer(test_data, input_cols = c("document"), output_col = "token")
expect_true("token" %in% colnames(transformed_data))
})
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