Validated; change optimizer naming in config

SymbioticLab · Dec 17, 2023 · 7918a28 · 7918a28
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commit 7918a28
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Showing 4 changed files with 4 additions and 4 deletions.
diff --git a/benchmark/configs/openimage/openimage.yml b/benchmark/configs/openimage/openimage.yml
@@ -51,7 +51,7 @@ job_conf:
     - device_conf_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_device_capacity     # Path of the client trace
     - device_avail_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_behave_trace
     - model: shufflenet_v2_x2_0                            # Models: e.g., shufflenet_v2_x2_0, mobilenet_v2, resnet34, albert-base-v2
-    - gradient_policy: yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
+    - gradient_policy: fed-yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
     - eval_interval: 30                     # How many rounds to run a testing on the testing set
     - rounds: 5000                          # Number of rounds to run this training. We use 1000 in our paper, while it may converge w/ ~400 rounds
     - filter_less: 21                       # Remove clients w/ less than 21 samples

diff --git a/benchmark/configs/others/local_dp.yml b/benchmark/configs/others/local_dp.yml
@@ -38,7 +38,7 @@ job_conf:
 #    - device_avail_file: /users/JIACHEN/FLPerf-Cluster/client_datamap/client_behave_trace
     - sample_mode: random                                  # Client selection: random, oort, random by default
     - model: resnet18                            # Models: shufflenet_v2_x2_0, mobilenet_v2, resnet34, albert-base-v2
-    - gradient_policy: fedavg                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
+    - gradient_policy: fed-avg                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
     - eval_interval: 10                     # How many rounds to run a testing on the testing set
     - rounds: 500                          # Number of rounds to run this training. We use 1000 in our paper, while it may converge w/ ~400 rounds
     - filter_less: 20

diff --git a/benchmark/configs/others/rl_conf.yml b/benchmark/configs/others/rl_conf.yml
@@ -48,7 +48,7 @@ job_conf:
     - device_conf_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_device_capacity     # Path of the client trace
     - device_avail_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_behave_trace
     - model: dqn                           # Models: e.g., shufflenet_v2_x2_0, mobilenet_v2, resnet34, albert-base-v2
-    - gradient_policy: yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
+    - gradient_policy: fed-yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
     - eval_interval: 50                     # How many rounds to run a testing on the testing set
     - rounds: 1000                          # Number of rounds to run this training. We use 1000 in our paper, while it may converge w/ ~400 rounds
     - filter_less: 21                       # Remove clients w/ less than 21 samples

diff --git a/benchmark/configs/speech/google_speech.yml b/benchmark/configs/speech/google_speech.yml
@@ -50,7 +50,7 @@ job_conf:
     - device_conf_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_device_capacity     # Path of the client trace
     - device_avail_file: $FEDSCALE_HOME/benchmark/dataset/data/device_info/client_behave_trace
     - model: resnet34                            # Models: e.g., shufflenet_v2_x2_0, mobilenet_v2, resnet34, albert-base-v2
-    - gradient_policy: yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
+    - gradient_policy: fed-yogi                 # {"fed-yogi", "fed-prox", "fed-avg"}, "fed-avg" by default
     - eval_interval: 30                     # How many rounds to run a testing on the testing set
     - rounds: 5000                          # Number of rounds to run this training. We use 1000 in our paper, while it may converge w/ ~400 rounds
     - filter_less: 21                       # Remove clients w/ less than 21 samples