first part of regression test

tests/regression_tests/apax_config.yaml

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+n_epochs: 1000
+seed: 0
+
+data:
+  directory: models/
+  experiment: apax
+
+  data_path: <PATH>
+
+  n_train: 1000
+  n_valid: 100
+
+  batch_size: 8
+  valid_batch_size: 100
+
+  shift_method: "per_element_regression_shift"
+  shift_options: {"energy_regularisation": 1.0}
+  shuffle_buffer_size: 1000
+
+  pos_unit: Ang
+  energy_unit: eV
+
+model:
+  n_basis: 7
+  n_radial: 5
+  nn: [512, 512]
+
+  r_max: 6.5
+  r_min: 0.5
+
+  calc_stress: false
+  use_zbl: true
+
+  b_init: normal
+  descriptor_dtype: fp32
+  readout_dtype: fp32
+  scale_shift_dtype: fp32
+
+metrics:
+  - name: energy
+    reductions:
+    - mae
+  - name: forces
+    reductions:
+    - mae
+    - mse
+  # - name: stress
+  #   reductions:
+  #   - mae
+  #   - mse
+
+loss:
+  - loss_type: structures
+    name: energy
+    weight: 1.0
+  - loss_type: structures
+    name: forces
+    weight: 8.0
+  - loss_type: cosine_sim
+    name: forces
+    weight: 0.1
+  # - loss_type: structures
+  #   name: stress
+  #   weight: 1.0
+
+optimizer:
+  opt_name: adam
+  opt_kwargs: {}
+  emb_lr: 0.003
+  nn_lr: 0.002
+  scale_lr: 0.0005
+  shift_lr: 0.025
+  zbl_lr: 0.001
+  transition_begin: 0
+
+callbacks:
+- name: csv
+
+checkpoints:
+  ckpt_interval: 1
+  # The options below are used for transfer learning
+  # base_model_checkpoint: null
+  # reset_layers: []
+
+progress_bar:
+  disable_epoch_pbar: false
+  disable_nl_pbar: false
+
+maximize_l2_cache: false

tests/regression_tests/test_apax_training.py

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+import pytest
+import pathlib
+import yaml
+from apax.train.run import run
+import urllib
+import zipfile
+import os
+
+TEST_PATH = pathlib.Path(__file__).parent.resolve()
+MD22_STACHYOSE_URL = "http://www.quantum-machine.org/gdml/repo/static/md22_stachyose.zip"
+
+@pytest.mark.slow
+def test_regression_model_training(get_tmp_path):
+    temp_path = get_tmp_path
+
+    #load dataset and safe it in temp_dir
+    data_path = temp_path / "data"
+    os.makedirs(data_path, exist_ok=True)
+    urllib.request.urlretrieve(MD22_STACHYOSE_URL, data_path / "md22_stachyose.zip")
+
+    with zipfile.ZipFile(data_path / "md22_stachyose.zip", "r") as zip_ref:
+        zip_ref.extractall(data_path)
+
+    input_file_path = (data_path / "md22_stachyose.xyz").as_posix()
+    output_file_path = (data_path / "md22_stachyose_mod.xyz").as_posix()
+    target_string = 'Energy'
+    replacement_string = 'energy'
+
+    replace_string_in_file(input_file_path, output_file_path, target_string, replacement_string)
+
+    #read and adjust config
+    confg_path = TEST_PATH / "apax_config.yaml"
+    with open(confg_path.as_posix(), "r") as stream:
+        config_dict = yaml.safe_load(stream)
+
+    config_dict["data"]["directory"] = temp_path.as_posix()
+    config_dict["data"]["data_path"] = output_file_path
+    config_dict["data"]["energy_unit"] = "kcal/mol"
+
+    run(config_dict)
+
+
+    assert False
+
+def replace_string_in_file(input_file_path, output_file_path, target_string, replacement_string):
+    with open(input_file_path, 'r') as input_file, open(output_file_path, 'w') as output_file:
+        for line in input_file:
+            # Replace all occurrences of the target string with the replacement string
+            modified_line = line.replace(target_string, replacement_string)
+            output_file.write(modified_line)