From d884686ace079d6f33b5e4f07fe5fdeaea6e2e2d Mon Sep 17 00:00:00 2001 From: PatReis Date: Wed, 15 Nov 2023 15:26:16 +0100 Subject: [PATCH] update for keras 3.0 --- kgcnn/literature/GAT/_make.py | 4 +- .../PAiNN_MatProjectJdft2dDataset_score.yaml | 154 ++++++++++++++++++ .../PAiNN_make_crystal_model/PAiNN_hyper.json | 1 + training/results/README.md | 1 + 4 files changed, 159 insertions(+), 1 deletion(-) create mode 100644 training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_MatProjectJdft2dDataset_score.yaml create mode 100644 training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_hyper.json diff --git a/kgcnn/literature/GAT/_make.py b/kgcnn/literature/GAT/_make.py index 83e1c469..6523e1eb 100644 --- a/kgcnn/literature/GAT/_make.py +++ b/kgcnn/literature/GAT/_make.py @@ -76,11 +76,13 @@ def make_model(inputs: list = None, Model inputs: Model uses the list template of inputs and standard output template. The supported inputs are :obj:`[nodes, edges, edge_indices, ...]` - with '...' indicating mask or id tensors following the template below: + with '...' indicating mask or ID tensors following the template below: + %s Model outputs: The standard output template: + %s diff --git a/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_MatProjectJdft2dDataset_score.yaml b/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_MatProjectJdft2dDataset_score.yaml new file mode 100644 index 00000000..4a8514a8 --- /dev/null +++ b/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_MatProjectJdft2dDataset_score.yaml @@ -0,0 +1,154 @@ +OS: nt_win32 +backend: tensorflow +cuda_available: 'False' +data_unit: meV/atom +date_time: '2023-11-15 15:22:58' +device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU'')]' +device_memory: '[]' +device_name: '[{}]' +epochs: +- 800 +- 800 +- 800 +- 800 +- 800 +execute_folds: null +kgcnn_version: 4.0.0 +learning_rate: +- 2.1409230612334795e-05 +- 2.1409230612334795e-05 +- 2.1409230612334795e-05 +- 2.1409230612334795e-05 +- 2.1409230612334795e-05 +loss: +- 0.01342229824513197 +- 0.01582755520939827 +- 0.015029882080852985 +- 0.016817400231957436 +- 0.014265685342252254 +max_learning_rate: +- 9.999999747378752e-05 +- 9.999999747378752e-05 +- 9.999999747378752e-05 +- 9.999999747378752e-05 +- 9.999999747378752e-05 +max_loss: +- 0.5201069712638855 +- 0.5315175652503967 +- 0.451824426651001 +- 0.5210411548614502 +- 0.4851284623146057 +max_scaled_mean_absolute_error: +- 75.4897232055664 +- 74.12128448486328 +- 61.5352897644043 +- 67.2265625 +- 57.95024871826172 +max_scaled_root_mean_squared_error: +- 149.78330993652344 +- 143.6664276123047 +- 140.2177734375 +- 131.99143981933594 +- 122.83416748046875 +max_val_loss: +- 0.2821546494960785 +- 0.3245273530483246 +- 0.3746875822544098 +- 0.5050886273384094 +- 0.618653416633606 +max_val_scaled_mean_absolute_error: +- 40.90802001953125 +- 45.22543716430664 +- 51.08058166503906 +- 65.11273956298828 +- 73.94288635253906 +max_val_scaled_root_mean_squared_error: +- 84.96401977539062 +- 111.83113861083984 +- 129.0309600830078 +- 159.9274444580078 +- 187.96551513671875 +min_learning_rate: +- 9.99999993922529e-09 +- 9.99999993922529e-09 +- 9.99999993922529e-09 +- 9.99999993922529e-09 +- 9.99999993922529e-09 +min_loss: +- 0.013281172141432762 +- 0.01350078172981739 +- 0.01428682915866375 +- 0.013030022382736206 +- 0.011631934903562069 +min_scaled_mean_absolute_error: +- 1.9360378980636597 +- 1.8882485628128052 +- 1.9466769695281982 +- 1.6665455102920532 +- 1.3933351039886475 +min_scaled_root_mean_squared_error: +- 9.1520357131958 +- 7.898106575012207 +- 9.539583206176758 +- 9.564427375793457 +- 6.542611122131348 +min_val_loss: +- 0.21616201102733612 +- 0.2801247239112854 +- 0.3179992735385895 +- 0.44068655371665955 +- 0.5248962044715881 +min_val_scaled_mean_absolute_error: +- 31.34011459350586 +- 39.01124572753906 +- 43.35005569458008 +- 56.815731048583984 +- 62.80753707885742 +min_val_scaled_root_mean_squared_error: +- 68.39794158935547 +- 100.04585266113281 +- 115.25602722167969 +- 143.70919799804688 +- 162.13404846191406 +model_class: make_crystal_model +model_name: PAiNN +model_version: '2023-10-04' +multi_target_indices: null +number_histories: 5 +scaled_mean_absolute_error: +- 1.9560686349868774 +- 2.2146451473236084 +- 2.046118974685669 +- 2.1549291610717773 +- 1.7081328630447388 +scaled_root_mean_squared_error: +- 9.223356246948242 +- 8.082352638244629 +- 9.63218879699707 +- 9.677685737609863 +- 6.588728427886963 +seed: 42 +time_list: +- '0:31:53.683697' +- '0:33:27.269425' +- '1:00:06.044732' +- '1:13:54.304826' +- '1:49:35.146251' +val_loss: +- 0.2428491860628128 +- 0.29850465059280396 +- 0.3226911723613739 +- 0.4874231219291687 +- 0.5294967293739319 +val_scaled_mean_absolute_error: +- 35.20934295654297 +- 41.602272033691406 +- 43.98591613769531 +- 62.783592224121094 +- 63.3631706237793 +val_scaled_root_mean_squared_error: +- 80.62264251708984 +- 101.75128936767578 +- 115.29129791259766 +- 147.98414611816406 +- 162.89393615722656 diff --git a/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_hyper.json b/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_hyper.json new file mode 100644 index 00000000..68329b48 --- /dev/null +++ b/training/results/MatProjectJdft2dDataset/PAiNN_make_crystal_model/PAiNN_hyper.json @@ -0,0 +1 @@ +{"model": {"module_name": "kgcnn.literature.PAiNN", "class_name": "make_crystal_model", "config": {"name": "PAiNN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "cast_disjoint_kwargs": {}, "input_node_embedding": {"input_dim": 95, "output_dim": 128}, "equiv_initialize_kwargs": {"dim": 3, "method": "eye"}, "bessel_basis": {"num_radial": 20, "cutoff": 5.0, "envelope_exponent": 5}, "pooling_args": {"pooling_method": "scatter_mean"}, "conv_args": {"units": 128, "cutoff": null, "conv_pool": "scatter_sum"}, "update_args": {"units": 128}, "depth": 2, "verbose": 10, "equiv_normalization": false, "node_normalization": false, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true], "units": [128, 1], "activation": ["swish", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 32, "epochs": 800, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearWarmupLinearLearningRateScheduler", "config": {"learning_rate_start": 0.0001, "learning_rate_stop": 1e-06, "epo_warmup": 25, "epo": 1000, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {"data_unit": "meV/atom"}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectJdft2dDataset", "module_name": "kgcnn.data.datasets.MatProjectJdft2dDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}, {"map_list": {"method": "count_nodes_and_edges", "total_edges": "total_ranges", "count_edges": "range_indices", "count_nodes": "node_number", "total_nodes": "total_nodes"}}]}} \ No newline at end of file diff --git a/training/results/README.md b/training/results/README.md index 76377c6f..1fecd2f6 100644 --- a/training/results/README.md +++ b/training/results/README.md @@ -138,6 +138,7 @@ Materials Project dataset from Matbench with 636 crystal structures and their co | model | kgcnn | epochs | MAE [meV/atom] | RMSE [meV/atom] | |:--------------------------|:--------|---------:|:-------------------------|:--------------------------| +| PAiNN.make_crystal_model | 4.0.0 | 800 | 49.3889 ± 11.5376 | 121.7087 ± 30.0472 | | Schnet.make_crystal_model | 4.0.0 | 800 | **45.2412 ± 11.6395** | **115.6890 ± 39.0929** | #### MatProjectLogGVRHDataset