diff --git a/eval/plot.py b/eval/plot.py
index 2782f2bd9098fa57ed553cd3914c775a405333d9..c185aa5dd23366d560149630eab24ec6f6c6762e 100644
--- a/eval/plot.py
+++ b/eval/plot.py
@@ -39,26 +39,43 @@ def plot_results(path):
folders.sort()
print("Reading folders from: ", path)
print("Folders: ", folders)
+ bytes_means, bytes_stdevs = {}, {}
for folder in folders:
folder_path = os.path.join(path, folder)
if not os.path.isdir(folder_path):
continue
results = []
- files = os.listdir(folder_path)
- files = [f for f in files if f.endswith("_results.json")]
- for f in files:
- filepath = os.path.join(folder_path, f)
- with open(filepath, "r") as inf:
- results.append(json.load(inf))
+ machine_folders = os.listdir(folder_path)
+ for machine_folder in machine_folders:
+ mf_path = os.path.join(folder_path, machine_folder)
+ if not os.path.isdir(mf_path):
+ continue
+ files = os.listdir(mf_path)
+ files = [f for f in files if f.endswith("_results.json")]
+ for f in files:
+ filepath = os.path.join(mf_path, f)
+ with open(filepath, "r") as inf:
+ results.append(json.load(inf))
+ # 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")
+ # Plot Testing loss
plt.figure(2)
means, stdevs, mins, maxs = get_stats([x["test_loss"] for x in results])
plot(means, stdevs, mins, maxs, "Testing Loss", folder, "upper right")
+ # Plot Testing Accuracy
plt.figure(3)
means, stdevs, mins, maxs = get_stats([x["test_acc"] for x in results])
plot(means, stdevs, mins, maxs, "Testing Accuracy", folder, "lower right")
+ # Collect total_bytes shared
+ bytes_list = []
+ for x in results:
+ max_key = str(max(list(map(int, x["total_bytes"].keys()))))
+ bytes_list.append({max_key: x["total_bytes"][max_key]})
+ means, stdevs, mins, maxs = get_stats(bytes_list)
+ bytes_means[folder] = list(means.values())[0]
+ bytes_stdevs[folder] = list(stdevs.values())[0]
plt.figure(1)
plt.savefig(os.path.join(path, "train_loss.png"))
@@ -66,6 +83,20 @@ def plot_results(path):
plt.savefig(os.path.join(path, "test_loss.png"))
plt.figure(3)
plt.savefig(os.path.join(path, "test_acc.png"))
+ # Plot total_bytes
+ plt.figure(4)
+ plt.title("Data Shared")
+ x_pos = np.arange(len(bytes_means.keys()))
+ plt.bar(
+ x_pos,
+ np.array(list(bytes_means.values())) // (1024 * 1024),
+ yerr=np.array(list(bytes_stdevs.values())) // (1024 * 1024),
+ align="center",
+ )
+ plt.ylabel("Total data shared in MBs")
+ plt.xlabel("Fraction of Model Shared")
+ plt.xticks(x_pos, list(bytes_means.keys()))
+ plt.savefig(os.path.join(path, "data_shared.png"))
def plot_parameters(path):
diff --git a/leaf.sh b/leaf.sh
deleted file mode 100755
index c4ab794ba1c8b932ef21364586d8629008f4ec1a..0000000000000000000000000000000000000000
--- a/leaf.sh
+++ /dev/null
@@ -1,11 +0,0 @@
-echo "[Cloning leaf repository]"
-git clone https://github.com/TalwalkarLab/leaf.git
-
-echo "[Installing unzip]"
-sudo apt-get install unzip
-
-cd leaf/data/shakespeare
-echo "[Generating non-iid data]"
-./preprocess.sh -s niid --sf 1.0 -k 0 -t sample -tf 0.8 --smplseed 10 --spltseed 10
-
-echo "[Data Generated]"
\ No newline at end of file
diff --git a/src/decentralizepy/sharing/PartialModel.py b/src/decentralizepy/sharing/PartialModel.py
index 424fdcbf7c0f362d211059dc058f9dc3f82154d9..bd01be3e66e0925e86ce7bb2474f8b6e4b0843fe 100644
--- a/src/decentralizepy/sharing/PartialModel.py
+++ b/src/decentralizepy/sharing/PartialModel.py
@@ -22,6 +22,7 @@ class PartialModel(Sharing):
log_dir,
alpha=1.0,
dict_ordered=True,
+ save_shared=False,
):
super().__init__(
rank, machine_id, communication, mapping, graph, model, dataset, log_dir
@@ -29,10 +30,17 @@ class PartialModel(Sharing):
self.alpha = alpha
self.dict_ordered = dict_ordered
self.communication_round = 0
- self.folder_path = os.path.join(
- self.log_dir, "shared_params/{}".format(self.rank)
- )
- Path(self.folder_path).mkdir(parents=True, exist_ok=True)
+ self.save_shared = save_shared
+
+ # Only save for 2 procs
+ if rank == 0 or rank == 1:
+ self.save_shared = True
+
+ if self.save_shared:
+ self.folder_path = os.path.join(
+ self.log_dir, "shared_params/{}".format(self.rank)
+ )
+ Path(self.folder_path).mkdir(parents=True, exist_ok=True)
def extract_top_gradients(self):
logging.info("Summing up gradients")
@@ -53,23 +61,24 @@ class PartialModel(Sharing):
with torch.no_grad():
_, G_topk = self.extract_top_gradients()
- shared_params = dict()
- shared_params["order"] = list(self.model.state_dict().keys())
- shapes = dict()
- for k, v in self.model.state_dict().items():
- shapes[k] = list(v.shape)
- shared_params["shapes"] = shapes
-
- shared_params[self.communication_round] = G_topk.tolist()
-
- with open(
- os.path.join(
- self.folder_path,
- "{}_shared_params.json".format(self.communication_round + 1),
- ),
- "w",
- ) as of:
- json.dump(shared_params, of)
+ if self.save_shared:
+ shared_params = dict()
+ shared_params["order"] = list(self.model.state_dict().keys())
+ shapes = dict()
+ for k, v in self.model.state_dict().items():
+ shapes[k] = list(v.shape)
+ shared_params["shapes"] = shapes
+
+ shared_params[self.communication_round] = G_topk.tolist()
+
+ with open(
+ os.path.join(
+ self.folder_path,
+ "{}_shared_params.json".format(self.communication_round + 1),
+ ),
+ "w",
+ ) as of:
+ json.dump(shared_params, of)
logging.info("Extracting topk params")
diff --git a/src/decentralizepy/utils.py b/src/decentralizepy/utils.py
index 75504417ffd181aa71184011ebc0fb1ea6996d52..a6bab0ddf4959363ad597c4ba0a160fa313ebc18 100644
--- a/src/decentralizepy/utils.py
+++ b/src/decentralizepy/utils.py
@@ -21,7 +21,10 @@ def get_args():
parser.add_argument("-ps", "--procs_per_machine", type=int, default=1)
parser.add_argument("-ms", "--machines", type=int, default=1)
parser.add_argument(
- "-ld", "--log_dir", type=str, default="./{}".format(datetime.datetime.now().isoformat(timespec='minutes'))
+ "-ld",
+ "--log_dir",
+ type=str,
+ default="./{}".format(datetime.datetime.now().isoformat(timespec="minutes")),
)
parser.add_argument("-is", "--iterations", type=int, default=1)
parser.add_argument("-cf", "--config_file", type=str, default="config.ini")