Custom Model MLP

class src.domain_classifier.custom_model_mlp.CustomDatasetMLP(df_data)

Bases: Dataset

__init__(df_data)

class src.domain_classifier.custom_model_mlp.MLP(input_dim, hidden_dim, output_dim)

Bases: Module

__init__(input_dim, hidden_dim, output_dim)

Initializes internal Module state, shared by both nn.Module and ScriptModule.

eval_model(eval_iterator, device='cuda', batch_size=8)

Evaluate trained model

Parameters:

• df_train (DataFrame) – Training dataframe

• epochs (int) – Number of epochs to train model

• device (str, optional (default=”cuda”)) – If “cuda”, a GPU is used if available

• batch_size (int, optiona (default=8)) – Batch size

forward(x)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.