From 4c73b35afe6b5dfb3eab13d70570ee3c5b826338 Mon Sep 17 00:00:00 2001
From: Jeffrey Wigger <jeffrey.wigger@epfl.ch>
Date: Wed, 15 Jun 2022 17:55:26 +0200
Subject: [PATCH] fixes jwins random walk
---
src/decentralizepy/node/Node.py | 1 +
src/decentralizepy/sharing/JwinsDPSGDAsync.py | 22 ++++---------------
2 files changed, 5 insertions(+), 18 deletions(-)
diff --git a/src/decentralizepy/node/Node.py b/src/decentralizepy/node/Node.py
index 8536b5c..033c1e5 100644
--- a/src/decentralizepy/node/Node.py
+++ b/src/decentralizepy/node/Node.py
@@ -519,6 +519,7 @@ class Node:
) as of:
json.dump(self.model.shared_parameters_counter.numpy().tolist(), of)
logging.info("disconnect neighbors")
+ print("Node: disconnect")
self.communication.disconnect_neighbors()
logging.info("Storing final weight")
# self.model.dump_weights(self.weights_store_dir, self.uid, iteration)
diff --git a/src/decentralizepy/sharing/JwinsDPSGDAsync.py b/src/decentralizepy/sharing/JwinsDPSGDAsync.py
index b0e0552..d40ceea 100644
--- a/src/decentralizepy/sharing/JwinsDPSGDAsync.py
+++ b/src/decentralizepy/sharing/JwinsDPSGDAsync.py
@@ -353,25 +353,11 @@ class JwinsDPSGDAsync(DPSGDRWAsync):
weight_vector = torch.ones_like(wt_params)
datas = []
batch = self._preprocessing_received_models()
+ new_batch = []
for n, vals in batch.items():
- if len(vals) > 1:
- data = None
- degree = 0
- # this should no longer happen, unless we get two rw from the same originator
- logging.info("averaging double messages for %i", n)
- for val in vals:
- degree_sub, iteration, data_sub = val
- if data is None:
- data = data_sub
- degree = degree
- else:
- for key, weight_val in data_sub.items():
- data[key] += weight_val
- degree = max(degree, degree_sub)
- for key, weight_val in data.items():
- data[key] /= len(vals)
- else:
- degree, iteration, data = vals[0]
+ new_batch.extend(vals)
+ for vals in new_batch:
+ degree, iteration, data = vals
#degree, iteration, data = self.peer_deques[n].popleft()
logging.debug(
"Averaging model from neighbor {} of iteration {}".format(
--
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