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continue keras core integration
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@PatReis
PatReis committed Sep 13, 2023
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200 changes: 102 additions & 98 deletions training_core/results/ESOLDataset/Schnet/Schnet_ESOLDataset_score.yaml
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@@ -1,7 +1,11 @@
OS: posix_linux
backend: tensorflow
OS: nt_win32
backend: torch
cuda_available: 'True'
data_unit: ''
date_time: '2023-09-08 16:32:16'
date_time: '2023-09-13 17:56:04'
device_id: '[0]'
device_memory: '[{''allocated'': 0.0, ''cached'': 0.1}]'
device_name: '[''NVIDIA GeForce GTX 1060 6GB'']'
epochs:
- 800
- 800
Expand All @@ -17,134 +21,134 @@ learning_rate:
- 1.06999996205559e-05
- 1.06999996205559e-05
loss:
- 0.012356339953839779
- 0.013351923786103725
- 0.013529826886951923
- 0.013422749936580658
- 0.013661202043294907
- 0.010011430829763412
- 0.012302489019930363
- 0.013542941771447659
- 0.01063549891114235
- 0.009813697077333927
max_learning_rate:
- 0.0005000000237487257
- 0.0005000000237487257
- 0.0005000000237487257
- 0.0005000000237487257
- 0.0005000000237487257
max_loss:
- 0.7113643884658813
- 0.7186248898506165
- 0.7084435224533081
- 0.7332432270050049
- 0.706541895866394
- 0.7063413262367249
- 0.7609256505966187
- 0.7159409523010254
- 0.7039654850959778
- 0.7093842625617981
max_scaled_mean_absolute_error:
- 1.4824234247207642
- 1.5330605506896973
- 1.5074206590652466
- 1.5363695621490479
- 1.503669261932373
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- 1.6069437265396118
- 1.5262893438339233
- 1.454487919807434
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max_scaled_root_mean_squared_error:
- 1.8612427711486816
- 1.9048391580581665
- 1.8831799030303955
- 2.121493101119995
- 1.863604187965393
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max_val_loss:
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- 0.4622005820274353
- 0.350281298160553
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max_val_scaled_mean_absolute_error:
- 0.9954290390014648
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- 0.7997042536735535
- 0.8752737641334534
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max_val_scaled_root_mean_squared_error:
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- 1.077497959136963
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min_learning_rate:
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- 1.06999996205559e-05
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min_loss:
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min_scaled_mean_absolute_error:
- 0.025462720543146133
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- 0.02940377965569496
- 0.028466414660215378
- 0.02892298437654972
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min_scaled_root_mean_squared_error:
- 0.07428765296936035
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- 0.08565159142017365
- 0.09151832014322281
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min_val_loss:
- 0.23827065527439117
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min_val_scaled_mean_absolute_error:
- 0.4522663950920105
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- 0.48299241065979004
- 0.4422135353088379
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- 0.3942352831363678
- 0.41914138197898865
- 0.48157763481140137
- 0.43868088722229004
min_val_scaled_root_mean_squared_error:
- 0.7140107750892639
- 0.5469481945037842
- 0.5934625267982483
- 0.6652877926826477
- 0.6266308426856995
- 0.6290794610977173
- 0.5576820373535156
- 0.618284285068512
- 0.6716180443763733
- 0.5965774655342102
model_class: make_model
model_name: Schnet
model_version: 2023.09.07
multi_target_indices: null
number_histories: 5
scaled_mean_absolute_error:
- 0.02621050924062729
- 0.02883092314004898
- 0.02940377965569496
- 0.028566351160407066
- 0.02940848283469677
- 0.02106151171028614
- 0.026483522728085518
- 0.029000014066696167
- 0.02257038839161396
- 0.021056318655610085
scaled_root_mean_squared_error:
- 0.07438243925571442
- 0.08620187640190125
- 0.08658499270677567
- 0.09151832014322281
- 0.08886461704969406
- 0.07620621472597122
- 0.091074638068676
- 0.09821934998035431
- 0.08720821142196655
- 0.07382410019636154
seed: 42
time_list:
- '0:04:27.346256'
- '0:04:26.197451'
- '0:04:30.127993'
- '0:04:31.160348'
- '0:04:32.070582'
- '0:20:17.603629'
- '0:19:09.172761'
- '0:21:18.667718'
- '0:20:18.305153'
- '0:19:49.705409'
val_loss:
- 0.2750350832939148
- 0.22051694989204407
- 0.23590177297592163
- 0.21229249238967896
- 0.2264338731765747
- 0.2412828654050827
- 0.2220507264137268
- 0.23384696245193481
- 0.2138018012046814
- 0.2256581038236618
val_scaled_mean_absolute_error:
- 0.48352858424186707
- 0.4216223955154419
- 0.4384129047393799
- 0.4986894130706787
- 0.4725487530231476
- 0.4590207040309906
- 0.4284597635269165
- 0.46461614966392517
- 0.49751242995262146
- 0.4585217833518982
val_scaled_root_mean_squared_error:
- 0.7575325965881348
- 0.583825409412384
- 0.607445240020752
- 0.7178400754928589
- 0.6797709465026855
- 0.6878407001495361
- 0.5926348567008972
- 0.680878758430481
- 0.6880843043327332
- 0.6271232962608337
2 changes: 1 addition & 1 deletion training_core/results/ESOLDataset/Schnet/Schnet_hyper.json
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{"model": {"class_name": "make_model", "module_name": "kgcnn.literature_core.Schnet", "config": {"name": "Schnet", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int32"}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32"}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64"}, {"shape": [], "name": "total_nodes", "dtype": "int64"}, {"shape": [], "name": "total_ranges", "dtype": "int64"}], "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true], "units": [64, 1], "activation": ["kgcnn>shifted_softplus", "linear"]}, "last_mlp": {"use_bias": [true, true], "units": [128, 64], "activation": ["kgcnn>shifted_softplus", "kgcnn>shifted_softplus"]}, "interaction_args": {"units": 128, "use_bias": true, "activation": "kgcnn>shifted_softplus", "cfconv_pool": "scatter_sum"}, "node_pooling_args": {"pooling_method": "scatter_sum"}, "depth": 4, "gauss_args": {"bins": 20, "distance": 4, "offset": 0.0, "sigma": 0.4}, "verbose": 10}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "scaler": {"class_name": "StandardScaler", "config": {"with_std": true, "with_mean": true, "copy": true}}, "fit": {"batch_size": 32, "epochs": 800, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.0005, "learning_rate_stop": 1e-05, "epo_min": 100, "epo": 800, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0005}}, "loss": "mean_absolute_error"}}, "data": {}, "dataset": {"class_name": "ESOLDataset", "module_name": "kgcnn.data.datasets.ESOLDataset", "config": {}, "methods": [{"set_attributes": {}}, {"map_list": {"method": "set_range", "max_distance": 4, "max_neighbours": 10000}}, {"map_list": {"method": "count_nodes_and_edges", "total_edges": "total_ranges", "count_edges": "range_indices"}}]}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}}
{"model": {"class_name": "make_model", "module_name": "kgcnn.literature_core.Schnet", "config": {"name": "Schnet", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int32"}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32"}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64"}, {"shape": [], "name": "total_nodes", "dtype": "int64"}, {"shape": [], "name": "total_ranges", "dtype": "int64"}], "cast_disjoint_kwargs": {"padded_disjoint": false}, "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true], "units": [64, 1], "activation": ["kgcnn>shifted_softplus", "linear"]}, "last_mlp": {"use_bias": [true, true], "units": [128, 64], "activation": ["kgcnn>shifted_softplus", "kgcnn>shifted_softplus"]}, "interaction_args": {"units": 128, "use_bias": true, "activation": "kgcnn>shifted_softplus", "cfconv_pool": "scatter_sum"}, "node_pooling_args": {"pooling_method": "scatter_sum"}, "depth": 4, "gauss_args": {"bins": 20, "distance": 4, "offset": 0.0, "sigma": 0.4}, "verbose": 10}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "scaler": {"class_name": "StandardScaler", "config": {"with_std": true, "with_mean": true, "copy": true}}, "fit": {"batch_size": 32, "epochs": 800, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.0005, "learning_rate_stop": 1e-05, "epo_min": 100, "epo": 800, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0005}}, "loss": "mean_absolute_error"}}, "data": {}, "dataset": {"class_name": "ESOLDataset", "module_name": "kgcnn.data.datasets.ESOLDataset", "config": {}, "methods": [{"set_attributes": {}}, {"map_list": {"method": "set_range", "max_distance": 4, "max_neighbours": 10000}}, {"map_list": {"method": "count_nodes_and_edges", "total_edges": "total_ranges", "count_edges": "range_indices"}}]}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}}
2 changes: 1 addition & 1 deletion training_core/train_graph.py
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Expand Up @@ -21,7 +21,7 @@
parser = argparse.ArgumentParser(description='Train a GNN on a Molecule dataset.')
parser.add_argument("--hyper", required=False, help="Filepath to hyperparameter config file (.py or .json).",
default="hyper/hyper_esol.py")
parser.add_argument("--category", required=False, help="Graph model to train.", default="GCN")
parser.add_argument("--category", required=False, help="Graph model to train.", default="Schnet")
parser.add_argument("--model", required=False, help="Graph model to train.", default=None)
parser.add_argument("--dataset", required=False, help="Name of the dataset.", default=None)
parser.add_argument("--make", required=False, help="Name of the class for model.", default=None)
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