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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")
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