From 9d09cccff134eeddd0d5ea86dda2a9d0b4d91da8 Mon Sep 17 00:00:00 2001
From: Rishi Sharma <rishi.sharma@epfl.ch>
Date: Wed, 11 Jan 2023 14:19:20 +0100
Subject: [PATCH] Add Bytes to CSVs, accuracy vs bytes plots
---
eval/plot.py | 88 +++++++++++++++++++++++++++++++++++++++++++++++++---
1 file changed, 83 insertions(+), 5 deletions(-)
diff --git a/eval/plot.py b/eval/plot.py
index a4374d3..a37e760 100644
--- a/eval/plot.py
+++ b/eval/plot.py
@@ -26,9 +26,9 @@ def get_stats(l):
return mean_dict, stdev_dict, min_dict, max_dict
-def plot(means, stdevs, mins, maxs, title, label, loc):
+def plot(means, stdevs, mins, maxs, title, label, loc, xlabel="communication rounds"):
plt.title(title)
- plt.xlabel("communication rounds")
+ plt.xlabel(xlabel)
x_axis = np.array(list(means.keys()))
y_axis = np.array(list(means.values()))
err = np.array(list(stdevs.values()))
@@ -37,6 +37,13 @@ def plot(means, stdevs, mins, maxs, title, label, loc):
plt.legend(loc=loc)
+def replace_dict_key(d_org: dict, d_other: dict):
+ result = {}
+ for x, y in d_org.items():
+ result[d_other[x]] = y
+ return result
+
+
def plot_results(path, centralized, data_machine="machine0", data_node=0):
folders = os.listdir(path)
if centralized.lower() in ["true", "1", "t", "y", "yes"]:
@@ -74,19 +81,54 @@ def plot_results(path, centralized, data_machine="machine0", data_node=0):
with open(folder_path / data_machine / f"{data_node}_results.json", "r") as f:
main_data = json.load(f)
main_data = [main_data]
+
+ # Plotting bytes over time
+ plt.figure(10)
+ b_means, stdevs, mins, maxs = get_stats([x["total_bytes"] for x in results])
+ plot(b_means, stdevs, mins, maxs, "Total Bytes", folder, "lower right")
+ df = pd.DataFrame(
+ {
+ "mean": list(b_means.values()),
+ "std": list(stdevs.values()),
+ "nr_nodes": [len(results)] * len(b_means),
+ },
+ list(b_means.keys()),
+ columns=["mean", "std", "nr_nodes"],
+ )
+ df.to_csv(
+ os.path.join(path, "total_bytes_" + folder + ".csv"), index_label="rounds"
+ )
+
# Plot Training loss
plt.figure(1)
means, stdevs, mins, maxs = get_stats([x["train_loss"] for x in results])
plot(means, stdevs, mins, maxs, "Training Loss", folder, "upper right")
+
+ correct_bytes = [b_means[x] for x in means]
+
df = pd.DataFrame(
{
"mean": list(means.values()),
"std": list(stdevs.values()),
"nr_nodes": [len(results)] * len(means),
+ "total_bytes": correct_bytes,
},
list(means.keys()),
- columns=["mean", "std", "nr_nodes"],
+ columns=["mean", "std", "nr_nodes", "total_bytes"],
)
+ plt.figure(11)
+ means = replace_dict_key(means, b_means)
+ plot(
+ means,
+ stdevs,
+ mins,
+ maxs,
+ "Training Loss",
+ folder,
+ "upper right",
+ "Total Bytes per node",
+ )
+
df.to_csv(
os.path.join(path, "train_loss_" + folder + ".csv"), index_label="rounds"
)
@@ -102,10 +144,24 @@ def plot_results(path, centralized, data_machine="machine0", data_node=0):
"mean": list(means.values()),
"std": list(stdevs.values()),
"nr_nodes": [len(results)] * len(means),
+ "total_bytes": correct_bytes,
},
list(means.keys()),
- columns=["mean", "std", "nr_nodes"],
+ columns=["mean", "std", "nr_nodes", "total_bytes"],
)
+ plt.figure(12)
+ means = replace_dict_key(means, b_means)
+ plot(
+ means,
+ stdevs,
+ mins,
+ maxs,
+ "Testing Loss",
+ folder,
+ "upper right",
+ "Total Bytes per node",
+ )
+
df.to_csv(
os.path.join(path, "test_loss_" + folder + ".csv"), index_label="rounds"
)
@@ -121,9 +177,22 @@ def plot_results(path, centralized, data_machine="machine0", data_node=0):
"mean": list(means.values()),
"std": list(stdevs.values()),
"nr_nodes": [len(results)] * len(means),
+ "total_bytes": correct_bytes,
},
list(means.keys()),
- columns=["mean", "std", "nr_nodes"],
+ columns=["mean", "std", "nr_nodes", "total_bytes"],
+ )
+ plt.figure(13)
+ means = replace_dict_key(means, b_means)
+ plot(
+ means,
+ stdevs,
+ mins,
+ maxs,
+ "Testing Accuracy",
+ folder,
+ "lower right",
+ "Total Bytes per node",
)
df.to_csv(
os.path.join(path, "test_acc_" + folder + ".csv"), index_label="rounds"
@@ -157,6 +226,15 @@ def plot_results(path, centralized, data_machine="machine0", data_node=0):
data_means[folder] = list(means.values())[0]
data_stdevs[folder] = list(stdevs.values())[0]
+ plt.figure(10)
+ plt.savefig(os.path.join(path, "total_bytes.png"), dpi=300)
+ plt.figure(11)
+ plt.savefig(os.path.join(path, "bytes_train_loss.png"), dpi=300)
+ plt.figure(12)
+ plt.savefig(os.path.join(path, "bytes_test_loss.png"), dpi=300)
+ plt.figure(13)
+ plt.savefig(os.path.join(path, "bytes_test_acc.png"), dpi=300)
+
plt.figure(1)
plt.savefig(os.path.join(path, "train_loss.png"), dpi=300)
plt.figure(2)
--
GitLab