Exemplo n.º 1
0
 def test_cartesian_prediction_distance_matrix_output(
         self, run_config, builder_config):
     loader_config = {
         "loader_type": "ts_loader",
         "load_kwargs": {
             "output_distance_matrix": True
         },
     }
     job = StructurePrediction({
         "name":
         "test",
         "run_config":
         run_config,
         "loader_config":
         loader_config,
         "builder_config":
         dict(**builder_config,
              builder_type="cartesian_builder",
              prediction_type="cartesians",
              output_type="distance_matrix"),
     })
     job.run()
Exemplo n.º 2
0
 def test_regression_to_structure_prediction_to_cross_validation(
         self, builder_config, run_config):
     job = Pipeline(jobs=[
         Regression(
             exp_config={
                 "run_config":
                 run_config,
                 "loader_config": {
                     "loader_type": "iso17_loader"
                 },
                 "builder_config":
                 dict(**builder_config, builder_type="force_builder"),
             }),
         StructurePrediction(
             exp_config={
                 "run_config":
                 run_config,
                 "loader_config": {
                     "loader_type": "qm9_loader",
                     "load_kwargs": {
                         "modify_structures": True
                     },
                 },
                 "builder_config":
                 dict(**builder_config, builder_type="cartesian_builder"),
             }),
         CrossValidate(
             exp_config={
                 "run_config":
                 run_config,
                 "loader_config": {
                     "loader_type": "ts_loader",
                     "splitting": 5
                 },
                 "builder_config":
                 dict(**builder_config, builder_type="cartesian_builder"),
             }),
     ])
     job.run()
     "seed": 1
 },
 jobs=[
     StructurePrediction(
         exp_config={
             "name": f"{Path(__file__).parent} QM9",
             "seed": 1,
             "run_config": {
                 "epochs": 100,
                 "test": True,
                 "batch_size": 32
             },
             "loader_config": {
                 "loader_type":
                 "isom_loader",
                 "path":
                 "/home/rjackson/dev/tensor-field-networks/data/isomerization/isomerization_dataset"
                 ".hd5f",
                 "splitting":
                 "75:20:5",
             },
             "builder_config": {
                 "builder_type": "cartesian_builder",
                 "radial_factory": "single_dense",
                 "prediction_type": "cartesians",
                 "output_type": "cartesians",
             },
         }),
     CrossValidate(
         exp_config={
             "name": f"{Path(__file__).parent} TS",
from pathlib import Path
from tfn.tools.jobs import Pipeline, CrossValidate, StructurePrediction


job = Pipeline(
    exp_config={"name": f"{Path(__file__).parent}", "seed": 1},
    jobs=[
        StructurePrediction(
            exp_config={
                "name": f"{Path(__file__).parent} QM9",
                "seed": 1,
                "run_config": {"epochs": 50, "test": False,},
                "loader_config": {
                    "loader_type": "qm9_loader",
                    "splitting": "90:10:0",
                    "load_kwargs": {"modify_structures": True, "custom_maxz": 36},
                },
                "builder_config": {
                    "builder_type": "cartesian_builder",
                    "radial_factory": "multi_dense",
                    "prediction_type": "cartesians",
                    "output_type": "cartesians",
                },
            }
        ),
        CrossValidate(
            exp_config={
                "name": f"{Path(__file__).parent} TS",
                "seed": 1,
                "run_config": {"epochs": 1000, "test": False, "batch_size": 48,},
                "loader_config": {
                    "loader_type": "ts_loader",
from pathlib import Path
from tfn.tools.jobs import StructurePrediction


job = StructurePrediction(
    exp_config={
        "name": f"{Path(__file__).parent}",
        "notes": "",
        "seed": 1,
        "run_config": {
            "epochs": 100,
            "test": True,
            "batch_size": 32,
        },
        "loader_config": {
            "loader_type": "isom_loader",
            "path": "/home/rjackson/dev/tensor-field-networks/data/isomerization/isomerization_dataset.hd5f",
            "splitting": "75:20:5",
        },
        "builder_config": {
            "builder_type": "cartesian_builder",
            "radial_factory": "multi_dense",
            "prediction_type": "cartesians",
            "output_type": "cartesians",
        },
        "lr_config": {"min_delta": 0.01, "patience": 30, "cooldown": 20},
    }
)
job.run()