parscanlogreader

Overview

The goal of parscanlogreader is to read and process raw log files from Scikit-learn’s RandomizedSearchCV.

Installation

The development version can be installed from GitHub with:

devtools::install_github("kreh-team/parscanlogreader")

Examples

Basic example

This is a basic example which shows you how the data pipeline works:

library(parscanlogreader)

src_file <- "logs/cnn-gru-scan.log"

log_data_raw <- src_file %>%
  read_raw_log() %>% 
  clean_log_data()

log_data <- log_data_raw %>%
  summarise_log_data()

Note that the functions are able to automatically parse the parameters params_list, numeric_params, num_folds, and num_models from the raw log files.

Manual parameter settings

If you want, you can manually set them yourself, as shown in the example below:

src_params_list <- c(
  "optimizers", "opt_recurrent_regs", "opt_kernel_regs", "opt_go_backwards",
  "opt_dropout_recurrent", "opt_dropout", "maxpool_size", "kernel_size",
  "gru_hidden_units", "filter_conv", "epochs", "batch_size", "activation_conv"
)
src_numeric_params <- c(
  "opt_dropout_recurrent", "opt_dropout", "maxpool_size", "kernel_size",
  "gru_hidden_units", "filter_conv", "epochs", "batch_size"
)

log_data_raw <- src_file %>%
  read_raw_log(
    params_list = src_params_list, 
    numeric_params = src_numeric_params
  ) %>%
  clean_log_data()

log_data <- log_data_raw %>%
  tidyr::drop_na() %>%
  summarise_log_data(
    params_list = src_params_list,
    num_folds = 5, 
    num_models = 50
  )