Error when attempting to run test installation script: tf2_gnn_train RGCN PPI --max-epochs 10 data/ppi/

[jfb54]

Seems to be related to the latest: merge pull request #38 from microsoft/mstan/expose-tffunc-disable

If you comment out the disable_tf_function_build argument in line 225 of model_utils.py, the code will run but then I hit issue #31

Error output is below:

E:\venv\Scripts\python.exe E:/venv/Scripts/tf2_gnn_train-script.py RGCN PPI --max-epochs 10 e:/data/ppi/
2021-01-24 15:07:15.212314: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
Setting random seed 0.
Trying to load task/model-specific default parameters from E:\repos\tf2-gnn\tf2_gnn\cli_utils\default_hypers\PPI_RGCN.json ... File found.
Dataset default parameters: {'max_nodes_per_batch': 10000, 'add_self_loop_edges': True, 'tie_fwd_bkwd_edges': False}
Loading data from e:/data/ppi/.
Loading PPI train data from e:/data/ppi/.
Loading PPI valid data from e:/data/ppi/.
Traceback (most recent call last):
Model default parameters: {'gnn_aggregation_function': 'sum', 'gnn_message_activation_function': 'relu', 'gnn_message_activation_before_aggregation': False, 'gnn_hidden_dim': 16, 'gnn_use_target_state_as_input': False, 'gnn_normalize_by_num_incoming': True, 'gnn_num_edge_MLP_hidden_layers': 0, 'gnn_message_calculation_class': 'RGCN', 'gnn_initial_node_representation_activation': 'tanh', 'gnn_dense_intermediate_layer_activation': 'tanh', 'gnn_num_layers': 4, 'gnn_dense_every_num_layers': 2, 'gnn_residual_every_num_layers': 2, 'gnn_use_inter_layer_layernorm': False, 'gnn_layer_input_dropout_rate': 0.0, 'gnn_global_exchange_mode': 'gru', 'gnn_global_exchange_every_num_layers': 2, 'gnn_global_exchange_weighting_fun': 'softmax', 'gnn_global_exchange_num_heads': 4, 'gnn_global_exchange_dropout_rate': 0.2, 'optimizer': 'Adam', 'learning_rate': 0.001, 'learning_rate_warmup_steps': None, 'learning_rate_decay_steps': None, 'momentum': 0.85, 'rmsprop_rho': 0.98, 'gradient_clip_value': None, 'gradient_clip_norm': None, 'gradient_clip_global_norm': None, 'use_intermediate_gnn_results': False}
File "E:/venv/Scripts/tf2_gnn_train-script.py", line 33, in
sys.exit(load_entry_point('tf2-gnn', 'console_scripts', 'tf2_gnn_train')())
File "E:\repos\tf2-gnn\tf2_gnn\cli\train.py", line 33, in run
Model parameters overridden by task/model defaults: {'gnn_num_layers': 4, 'gnn_hidden_dim': 320, 'gnn_use_target_state_as_input': False, 'gnn_normalize_by_num_incoming': True, 'gnn_num_edge_MLP_hidden_layers': 0, 'gnn_layer_input_dropout_rate': 0.1, 'gnn_dense_every_num_layers': 10000, 'gnn_residual_every_num_layers': 10000, 'gnn_global_exchange_every_num_layers': 10000, 'gnn_use_inter_layer_layernorm': False, 'gnn_initial_node_representation_activation': 'tanh', 'gnn_dense_intermediate_layer_activation': 'tanh', 'gnn_message_activation_function': 'ReLU', 'gnn_aggregation_function': 'sum'}
lambda: run_train_from_args(args, hyperdrive_hyperparameter_overrides), args.debug
File "E:\venv\lib\site-packages\dpu_utils\utils\debughelper.py", line 21, in run_and_debug
func()
File "E:\repos\tf2-gnn\tf2_gnn\cli\train.py", line 33, in
lambda: run_train_from_args(args, hyperdrive_hyperparameter_overrides), args.debug
File "E:\repos\tf2-gnn\tf2_gnn\cli_utils\training_utils.py", line 165, in run_train_from_args
disable_tf_function_build=args.disable_tf_func,
File "E:\repos\tf2-gnn\tf2_gnn\cli_utils\model_utils.py", line 310, in get_model_and_dataset
disable_tf_function_build=disable_tf_function_build,
File "E:\repos\tf2-gnn\tf2_gnn\cli_utils\model_utils.py", line 225, in get_model
model_params, dataset=dataset, disable_tf_function_build=disable_tf_function_build
TypeError: init() got an unexpected keyword argument 'disable_tf_function_build'

Process finished with exit code 1

[brunaostii]

I have the same issue, please let me know if you fix the problem

[mmjb]

Sorry, I was on paternity leave and somehwat ignored these things. @brunaostii, can you please verify that the branch dev/mabrocks/tffunc_disable_fixes that I just pushed fixes the problem for you?