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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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@ -55,6 +55,46 @@ class Config:
If you are not sure that all parameters are included in the config file then you can set the default values or default_factory with the field element in the dataclass. see [dataclass](https://davrot.github.io/pytutorial/python_basics/dataclass/) for details.
Here is an extra example how this could look like:
```python
@dataclass
class LearningParameters:
"""Parameter required for training"""
learning_active: bool = field(default=True)
loss_mode: int = field(default=0)
loss_coeffs_mse: float = field(default=0.5)
loss_coeffs_kldiv: float = field(default=1.0)
optimizer_name: str = field(default="Adam")
learning_rate_gamma_w: float = field(default=-1.0)
learning_rate_threshold_w: float = field(default=0.00001)
lr_schedule_name: str = field(default="ReduceLROnPlateau")
lr_scheduler_use_performance: bool = field(default=False)
lr_scheduler_factor_w: float = field(default=0.75)
lr_scheduler_patience_w: int = field(default=-1)
lr_scheduler_tau_w: int = field(default=10)
number_of_batches_for_one_update: int = field(default=1)
overload_path: str = field(default="Previous")
weight_noise_range: list[float] = field(default_factory=list)
eps_xy_intitial: float = field(default=1.0)
disable_scale_grade: bool = field(default=False)
kepp_last_grad_scale: bool = field(default=True)
sbs_skip_gradient_calculation: list[bool] = field(default_factory=list)
adapt_learning_rate_after_minibatch: bool = field(default=True)
w_trainable: list[bool] = field(default_factory=list)
```
## The JSON config file
Here an example JSON file tailored for our dataclass Config: