File size: 2,883 Bytes
998922f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | #!/usr/bin/env Rscript
library(tidyverse)
library(dplyr)
library(readr)
library(openxlsx)
library(ggmagnify)
library(optparse)
library(this.path)
# make reference to library function portable
source(file.path(here("functions"), "utils.R"))
source(file.path(here("functions"), "allocation.R"))
# plot_sensi_vs_ablation <- function()
plot_meta <- function(
model_id,
the_dataset,
df_disp,
df_hqq) {
min_ppl <- min(df_disp$ppl)
max_ppl <- max(df_disp$ppl)
min_ppl <- floor(min_ppl * 10) / 10
max_ppl <- ceiling(max_ppl * 10) / 10
step <- round((max_ppl - min_ppl) / 15, digits = 2)
plt <- ggplot(df_disp, aes(bpp, ppl, color = ablation)) +
# scale_x_continuous(
# limits = c(0, 9.0),
# breaks = seq(0, 9.0, 0.50)
# ) +
# scale_y_continuous(
# limits = c(min_ppl, max_ppl),
# breaks = seq(min_ppl, max_ppl, step)
# ) +
geom_point(size = 2) +
labs(x = "% Memory Increment", y = "Perplexity") +
theme(
strip.background = element_rect(
color = "darkgray", fill = "white", linewidth = 1.0, linetype = "solid"
),
strip.text.x = element_text(face = "bold", size = 12),
strip.text.y = element_text(face = "bold", size = 12),
legend.position = "bottom"
) +
# guides(
# shape = guide_legend(title = legend_title),
# color = guide_legend(title = legend_title)
# ) +
facet_grid(method ~ model, scales = "free")
ggsave(
# paste0("pdfs/ppl-", type, "-", model_id, "-", the_dataset, ".pdf"),
"pdfs/abc.pdf",
plot = plt,
width = 8,
height = 6,
dpi = 600
)
return(plt)
}
parser <- OptionParser()
parser <- add_option(
parser, c("-d", "--combined_csv_file"),
type = "character",
help = "The combined csv file",
metavar = "character"
)
parser <- add_option(
parser, c("-a", "--allot_csv_file"),
type = "character",
help = "Allocation CSV file",
metavar = "character"
)
parser <- add_option(
parser, c("-t", "--type"),
type = "character",
help = "Type diagram",
metavar = "character"
)
args <- parse_args(parser)
if (is.null(args$csv_file)) {
combined_csv_fp <- "data/combined.csv"
} else {
combined_csv_fp <- args$combined_csv_file
}
if (is.null(args$csv_file)) {
allot_cfg_csv_fp <- "data/quant-cfg-allocation.csv"
} else {
allot_cfg_csv_fp <- args$allot_csv_file
}
if (is.null(args$type)) {
type <- "sensi-vs-kurt"
} else {
type <- args$type
}
# TODO: remove debug lines
allot_cfg_csv_fp <- "endeavors/boost/data/quant-cfg-allocation.csv"
combined_csv_fp <- "endeavors/boost/data/combined.csv"
tup <- load_ppl_mem_inc(allot_cfg_csv_fp, combined_csv_fp)
df_ppl_mem_inc <- tup[[1]]
df_hqq <- tup[[2]]
# models <- unique(df_ppl_mem_inc$model)
model_id <- "Llama-2-7B"
plt <- plot_meta(
model_id,
"C4",
df_ppl_mem_inc |> filter(model == model_id & dataset == "C4"),
df_hqq
)
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