| from transformers import PretrainedConfig, AutoConfig | |
| class MLPConfig(PretrainedConfig): | |
| r""" | |
| Config for the MLP model. | |
| Args: | |
| embedding_size (int, 8): Size of the input embeddings (last dimension of the 3D input). | |
| sequence_length (int, 8): Number of tokens in input sequence (middle dimension; must be fixed). | |
| num_labels (int, 32): Number of output labels (for multi-label classification). | |
| hidden_size (int, 2048): Size of each hidden layer. | |
| num_hidden_layers (int, 3): How many hidden layers to stack. | |
| dropout (float, 0.1): Dropout probability for hidden layers. | |
| """ | |
| model_type = "mlp" | |
| def __init__( | |
| self, | |
| embedding_size=8, | |
| sequence_length=8, | |
| num_labels=32, | |
| hidden_size=2048, | |
| num_hidden_layers=3, | |
| dropout=0.1, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.embedding_size = embedding_size | |
| self.sequence_length = sequence_length | |
| self.num_labels = num_labels | |
| self.hidden_size = hidden_size | |
| self.num_hidden_layers = num_hidden_layers | |
| self.dropout = dropout | |
| AutoConfig.register("mlp", MLPConfig) | |