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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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 | library(tidyverse)
library(ggthemes)
library(ggbreak)
library(readr)
all_cols <- c(
"model", "algo", "config",
"bpp", "ppl_wikitext", "ppl_c4"
)
df_all <- read_csv("data/combined.csv") |>
select(all_of(all_cols)) |>
filter(
algo == "mxq" | algo == "pct5" | algo == "pct6" | algo == "fp16" | algo == "awq" | algo == "hqq"
) |>
mutate(
model = factor(
model,
levels = c("Llama-2-7b-hf", "Meta-Llama-3-8B", "Llama-2-13b-hf"),
labels = c("Llama-2-7B", "Llama-3-8B", "Llama-2-13B")
),
algo = factor(
algo,
levels = c("mxq", "pct5", "pct6", "fp16", "awq", "gptq", "bnb", "hqq"),
labels = c("MXQ", "PCT5", "PCT6", "FP16", "AWQ", "GPTQ", "BnB", "HQQ"),
)
)
df_wikitxt_all <- df_all |>
rename(ppl = ppl_wikitext)
df_c4_all <- df_all |>
rename(ppl = ppl_c4)
# Plot Llama-2-13b memory drop vs PPL loss ---------------------------------
model_name <- "Llama-2-13B"
df_wikitxt <- df_wikitxt_all |>
filter(
model == model_name & bpp >= 2.5
)
min_ppl <- min(df_wikitxt$ppl)
min_bpp <- min(df_wikitxt$bpp)
plt1 <- ggplot(
subset(df_wikitxt, algo != "MXQ"),
aes(x = bpp, y = ppl),
) +
geom_point(
data = subset(df_wikitxt, algo == "MXQ"),
size = 0.5,
aes(shape = algo, color = algo, y = ppl)
) +
geom_point(size = 1.5, aes(shape = algo, color = algo, y = ppl)) +
geom_hline(
yintercept = min_ppl * 1.02,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
geom_hline(
yintercept = min_ppl * 1.01,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
geom_hline(
yintercept = min_ppl,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
annotate("text", x = 15.8, y = min_ppl * 1.00, label = "FP16") +
scale_x_break(c(5.5, 15.6)) +
scale_x_continuous(
limits = c(2.8, 16.2),
breaks = seq(2.8, 5.5, 0.20),
sec.axis = sec_axis(~ 100 * (16 - .) / 16, name = "% Memery Reduction")
) +
scale_y_continuous(
limits = c(min_ppl * 0.99, min_ppl * 1.20),
breaks = seq(4.63, 4.63 * 1.20, 0.20),
sec.axis = sec_axis(~ 100 * (. - 4.63) / 4.63, name = "% Degradation")
) +
labs(x = "Bit Budget", y = "Perplexity") +
theme_gray(base_size = 14) +
guides(
shape = guide_legend(title = "Method:"),
color = guide_legend(title = "Method:")
) +
theme(
legend.position = "bottom",
legend.text = element_text(size = 14),
legend.title = element_text(size = 14)
) +
facet_wrap(~model, scales = "free") +
scale_color_solarized()
plt1
ggsave(
paste0("pdfs/", "ppl-wikitext-", model_name, ".pdf"),
plot = plt1, width = 8, height = 6
)
df_c4 <- df_c4_all |>
filter(
grepl(model_name, model) & bpp >= 2.5
)
min_ppl <- min(df_c4$ppl)
min_bpp <- min(df_c4$bpp)
plt2 <- ggplot(
subset(df_c4, algo != "MXQ"),
aes(x = bpp, y = ppl),
) +
geom_point(
data = subset(df_c4, algo == "MXQ"),
size = 0.5,
aes(shape = algo, color = algo, y = ppl)
) +
geom_point(size = 1.5, aes(shape = algo, color = algo, y = ppl)) +
geom_hline(
yintercept = min_ppl * 1.02,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
geom_hline(
yintercept = min_ppl * 1.01,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
geom_hline(
yintercept = min_ppl,
linetype = "dashed",
size = 0.1,
color = "blue"
) +
annotate("text", x = 15.8, y = min_ppl * 1.00, label = "FP16") +
scale_x_break(c(5.5, 15.6)) +
scale_x_continuous(
limits = c(2.8, 16.2),
breaks = seq(2.8, 5.5, 0.20),
sec.axis = sec_axis(~ 100 * (16 - .) / 16, name = "% Memery Reduction")
) +
scale_y_continuous(
limits = c(min_ppl * 0.99, min_ppl * 1.20),
breaks = seq(6.45, 6.45 * 1.20, 0.20),
sec.axis = sec_axis(~ 100 * (. - 6.45) / 6.45, name = "% Degradation")
) +
labs(x = "Bit Budget", y = "Perplexity") +
theme_gray(base_size = 14) +
guides(
shape = guide_legend(title = "Method:"),
color = guide_legend(title = "Method:")
) +
theme(
legend.position = "bottom",
legend.text = element_text(size = 14),
legend.title = element_text(size = 14)
) +
facet_wrap(~model, scales = "free") +
scale_color_solarized()
plt2
ggsave(
paste0("pdfs/", "mxq-c4-", model_name, ".pdf"),
plot = plt2, width = 8, height = 6
)
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