Update homogeneous unit test (#772)

*Issue #, if available:* *Description of changes:* By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice. Co-authored-by: Xiang Song <[email protected]>
awslabs · Mar 15, 2024 · e9823ce · e9823ce
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diff --git a/tests/end2end-tests/data_process/homogeneous_test.sh b/tests/end2end-tests/data_process/homogeneous_test.sh
@@ -27,11 +27,11 @@ python3 -m graphstorm.gconstruct.construct_graph --conf-file $GS_HOME/tests/end2
 error_and_exit $?
 
 echo "********* Test Node Classification on GConstruct Homogeneous Graph ********"
-python3 -m graphstorm.run.gs_node_classification --workspace $GS_HOME/training_scripts/gsgnn_np/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_nc.yaml --target-ntype _N
+python3 -m graphstorm.run.gs_node_classification --workspace $GS_HOME/training_scripts/gsgnn_np/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_nc.yaml --target-ntype _N --model-encoder-type sage
 error_and_exit $?
 
 echo "********* Test Edge Classification on GConstruct Homogeneous Graph ********"
-python3 -m graphstorm.run.gs_edge_classification --workspace $GS_HOME/training_scripts/gsgnn_ep/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_ec.yaml --target-etype _N,_E,_N
+python3 -m graphstorm.run.gs_edge_classification --workspace $GS_HOME/training_scripts/gsgnn_ep/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_ec.yaml --target-etype _N,_E,_N --model-encoder-type sage
 error_and_exit $?
 
 echo "********* Test Homogeneous Graph Optimization on reverse edge********"
@@ -42,11 +42,11 @@ python3 $GS_HOME/tests/end2end-tests/data_process/check_homogeneous.py
 error_and_exit $?
 
 echo "********* Test Node Classification on GConstruct Homogeneous Graph with reverse edge********"
-python3 -m graphstorm.run.gs_node_classification --workspace $GS_HOME/training_scripts/gsgnn_np/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous_rev/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_nc.yaml --target-ntype _N
+python3 -m graphstorm.run.gs_node_classification --workspace $GS_HOME/training_scripts/gsgnn_np/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous_rev/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_nc.yaml --target-ntype _N --model-encoder-type gat
 error_and_exit $?
 
 echo "********* Test Edge Classification on GConstruct Homogeneous Graph with reverse edge********"
-python3 -m graphstorm.run.gs_edge_classification --workspace $GS_HOME/training_scripts/gsgnn_ep/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous_rev/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_ec.yaml --target-etype _N,_E,_N
+python3 -m graphstorm.run.gs_edge_classification --workspace $GS_HOME/training_scripts/gsgnn_ep/ --num-trainers $NUM_TRAINERS --num-servers 1 --num-samplers 0 --part-config /tmp/movielen_100k_train_val_1p_4t_homogeneous_rev/movie-lens-100k.json --ip-config ip_list.txt --ssh-port 2222 --cf ml_ec.yaml --target-etype _N,_E,_N --model-encoder-type gat
 error_and_exit $?
 
 echo "********* Test Node Classification with homogeneous graph optimization********"

diff --git a/training_scripts/gsgnn_ep/ml_ec_homogeneous.yaml b/training_scripts/gsgnn_ep/ml_ec_homogeneous.yaml
@@ -6,7 +6,7 @@ gsf:
     verbose: false
     save_perf_results_path: null
   gnn:
-    model_encoder_type: rgcn
+    model_encoder_type: sage
     fanout: "4"
     num_layers: 1
     hidden_size: 128

diff --git a/training_scripts/gsgnn_np/ml_nc_homogeneous.yaml b/training_scripts/gsgnn_np/ml_nc_homogeneous.yaml
@@ -6,7 +6,7 @@ gsf:
     verbose: false
     save_perf_results_path: null
   gnn:
-    model_encoder_type: rgcn
+    model_encoder_type: sage
     fanout: "4"
     num_layers: 1
     hidden_size: 128