neurovlm.training.MLPTextToBrainTrainConfig#
- class neurovlm.training.MLPTextToBrainTrainConfig(output_root: 'str | Path' = 'runs', run_id: 'str | None' = None, seed: 'int' = 42, device: 'str' = 'auto', epochs: 'int' = 100, batch_size: 'int' = 256, eval_batch_size: 'int | None' = None, num_workers: 'int' = 0, learning_rate: 'float' = 5e-05, weight_decay: 'float' = 0.0, gradient_clip: 'float | None' = None, early_stopping_patience: 'int | None' = None, early_stopping_min_delta: 'float' = 0.0, max_train_batches: 'int | None' = None, max_eval_batches: 'int | None' = None, resume: 'str | Path | None' = None, preset: 'str' = 'retained', text_dim: 'int' = 768, hidden_dim: 'int' = 512, latent_dim: 'int' = 384, brain_dim: 'int' = 28542, primary_metric: 'str' = 'val_loss', metric_direction: 'MetricDirection' = <MetricDirection.MIN: 'min'>)[source]#
- Parameters:
output_root (str | Path)
run_id (str | None)
seed (int)
device (str)
epochs (int)
batch_size (int)
eval_batch_size (int | None)
num_workers (int)
learning_rate (float)
weight_decay (float)
gradient_clip (float | None)
early_stopping_patience (int | None)
early_stopping_min_delta (float)
max_train_batches (int | None)
max_eval_batches (int | None)
resume (str | Path | None)
preset (str)
text_dim (int)
hidden_dim (int)
latent_dim (int)
brain_dim (int)
primary_metric (str)
metric_direction (MetricDirection)
- __init__(output_root='runs', run_id=None, seed=42, device='auto', epochs=100, batch_size=256, eval_batch_size=None, num_workers=0, learning_rate=5e-05, weight_decay=0.0, gradient_clip=None, early_stopping_patience=None, early_stopping_min_delta=0.0, max_train_batches=None, max_eval_batches=None, resume=None, preset='retained', text_dim=768, hidden_dim=512, latent_dim=384, brain_dim=28542, primary_metric='val_loss', metric_direction=MetricDirection.MIN)#
- Parameters:
output_root (str | Path)
run_id (str | None)
seed (int)
device (str)
epochs (int)
batch_size (int)
eval_batch_size (int | None)
num_workers (int)
learning_rate (float)
weight_decay (float)
gradient_clip (float | None)
early_stopping_patience (int | None)
early_stopping_min_delta (float)
max_train_batches (int | None)
max_eval_batches (int | None)
resume (str | Path | None)
preset (str)
text_dim (int)
hidden_dim (int)
latent_dim (int)
brain_dim (int)
primary_metric (str)
metric_direction (MetricDirection)
- Return type:
None
Methods
__init__([output_root, run_id, seed, ...])architecture()Attributes
batch_sizebrain_dimdeviceearly_stopping_min_deltaearly_stopping_patienceepochseval_batch_sizegradient_cliphidden_dimlatent_dimlearning_ratemax_eval_batchesmax_train_batchesmetric_directionnum_workersoutput_rootpresetprimary_metricresumerun_idseedtext_dimweight_decay