Nothing
context("Testing model save")
source("helper-utils.R")
check_contents <- function(path) {
dir_contents <- dir(path, recursive = TRUE)
expect_true(any(grepl("saved_model\\.pb", dir_contents)))
expect_true(any(grepl("variables\\.data", dir_contents)))
expect_true(any(grepl("variables\\.index", dir_contents)))
unlink(path, recursive = TRUE)
}
export_test_savedmodel <- function(model) {
temp_path <- file.path(tempfile(), "testthat-save")
if (dir.exists(temp_path)) unlink(temp_path, recursive = TRUE)
export_savedmodel(model, temp_path, overwrite = FALSE)
check_contents(temp_path)
}
test_succeeds("export_savedmodel() runs successfully for linear_regressor", {
specs <- mtcars_regression_specs()
model <- linear_regressor(feature_columns = specs$linear_feature_columns)
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
test_succeeds("export_savedmodel() runs successfully for dnn_linear_combined_regressor", {
specs <- mtcars_regression_specs()
model <- dnn_linear_combined_regressor(
linear_feature_columns = specs$linear_feature_columns,
dnn_feature_columns = specs$dnn_feature_columns,
dnn_hidden_units = c(3, 3))
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
test_succeeds("export_savedmodel() runs successfully for dnn_regressor", {
specs <- mtcars_regression_specs()
model <- dnn_regressor(
hidden_units = c(3,3),
feature_columns = specs$linear_feature_columns
)
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
test_succeeds("export_savedmodel() runs successfully for linear_classifier", {
specs <- mtcars_classification_specs()
model <- linear_classifier(feature_columns = specs$linear_feature_columns)
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
test_succeeds("export_savedmodel() runs successfully for dnn_linear_combined_classifier", {
specs <- mtcars_classification_specs()
model <- dnn_linear_combined_classifier(
linear_feature_columns = specs$linear_feature_columns,
dnn_feature_columns = specs$dnn_feature_columns,
dnn_hidden_units = c(3, 3))
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
test_succeeds("export_savedmodel() runs successfully for dnn_classifier", {
specs <- mtcars_classification_specs()
model <- dnn_classifier(
hidden_units = c(3,3),
feature_columns = specs$linear_feature_columns
)
model %>% train(input_fn = specs$input_fn, steps = 2)
export_test_savedmodel(model)
})
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