phlower.settings.PhlowerTrainerSetting

class phlower.settings.PhlowerTrainerSetting(*, loss_setting, optimizer_setting=<factory>, scheduler_setting=<factory>, n_epoch=10, random_seed=0, batch_size=1, num_workers=0, device='cpu', evaluation_for_training=True, non_blocking=False)

Bases: BaseModel

Methods

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
loss_setting	setting for loss function
optimizer_setting	setting for optimizer
scheduler_setting	setting for schedulers
n_epoch	the number of epochs.
random_seed	random seed.
batch_size	batch size.
num_workers	the number of cores.
device	device name.
evaluation_for_training	If True, evaluation for training dataset is performed
non_blocking

Parameters:

• loss_setting (LossSetting)

• optimizer_setting (OptimizerSetting)

• scheduler_setting (list[SchedulerSetting])

• n_epoch (int)

• random_seed (int)

• batch_size (int)

• num_workers (int)

• device (str)

• evaluation_for_training (bool)

• non_blocking (bool)

batch_size: int

batch size. Defaults to 1

device: str

device name. Defaults to cpu

evaluation_for_training: bool

If True, evaluation for training dataset is performed

loss_setting: LossSetting

setting for loss function

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

n_epoch: int

the number of epochs. Defaults to 10.

num_workers: int

the number of cores. Defaults to 0.

optimizer_setting: OptimizerSetting

setting for optimizer

random_seed: int

random seed. Defaults to 0

scheduler_setting: list[SchedulerSetting]

setting for schedulers