modeling_mlp.py

import torch

from transformers import PreTrainedModel

from .configuration_mlp import MLPConfig


class MLP(PreTrainedModel):
    config_class = MLPConfig

    def __init__(self, config):
        super().__init__(config)
        self.input_layer = torch.nn.Linear(config.input_size, config.hidden_size)
        self.mid_layer = torch.nn.Linear(config.hidden_size, config.hidden_size)
        self.output_layer = torch.nn.Linear(config.hidden_size, config.output_size)

    def forward(self, inputs):
        x = torch.nn.functional.relu(self.input_layer(inputs))
        x = torch.nn.functional.relu(self.mid_layer(x))
        return torch.nn.functional.softmax(self.output_layer(x), dim=-1)

MLP.register_for_auto_class("AutoModel")