vame.model.evaluate
Variational Animal Motion Embedding 0.1 Toolbox © K. Luxem & P. Bauer, Department of Cellular Neuroscience Leibniz Institute for Neurobiology, Magdeburg, Germany
https://github.com/LINCellularNeuroscience/VAME Licensed under GNU General Public License v3.0
plot_reconstruction
def plot_reconstruction(filepath: str,
test_loader: Data.DataLoader,
seq_len_half: int,
model: RNN_VAE,
model_name: str,
FUTURE_DECODER: bool,
FUTURE_STEPS: int,
suffix: Optional[str] = None) -> None
Plot the reconstruction and future prediction of the input sequence.
Arguments:
filepath
str - Path to save the plot.test_loader
Data.DataLoader - DataLoader for the test dataset.seq_len_half
int - Half of the temporal window size.model
RNN_VAE - Trained VAE model.model_name
str - Name of the model.FUTURE_DECODER
bool - Flag indicating whether the model has a future prediction decoder.FUTURE_STEPS
int - Number of future steps to predict.suffix
Optional[str], optional - Suffix for the saved plot filename. Defaults to None.
plot_loss
def plot_loss(cfg: dict, filepath: str, model_name: str) -> None
Plot the losses of the trained model.
Arguments:
cfg
dict - Configuration dictionary.filepath
str - Path to save the plot.model_name
str - Name of the model.
eval_temporal
def eval_temporal(cfg: dict,
use_gpu: bool,
model_name: str,
fixed: bool,
snapshot: Optional[str] = None,
suffix: Optional[str] = None) -> None
Evaluate the temporal aspects of the trained model.
Arguments:
cfg
dict - Configuration dictionary.use_gpu
bool - Flag indicating whether to use GPU for evaluation.model_name
str - Name of the model.fixed
bool - Flag indicating whether the data is fixed or not.snapshot
Optional[str], optional - Path to the model snapshot. Defaults to None.suffix
Optional[str], optional - Suffix for the saved plot filename. Defaults to None.
evaluate_model
@save_state(model=EvaluateModelFunctionSchema)
def evaluate_model(config: str,
use_snapshots: bool = False,
save_logs: bool = False) -> None
Evaluate the trained model.
Arguments:
config
str - Path to config file.use_snapshots
bool, optional - Whether to plot for all snapshots or only the best model. Defaults to False.