Model.py

import torch
from torch import nn

class RecogJoint(nn.Module):
    def __init__(self):
        super(RecogJoint, self).__init__()
        self.dense1 = nn.Linear(63,512)
        self.batch_norm1 = nn.BatchNorm1d(512)
        self.dropout1 = nn.Dropout(0.3)
        self.dense2 = nn.Linear(512,512)
        self.batch_norm2 = nn.BatchNorm1d(512)
        self.dropout2 = nn.Dropout(0.3)
        self.dense3 = nn.Linear(512,512)
        self.batch_norm3 = nn.BatchNorm1d(512)
        self.dropout3 = nn.Dropout(0.3)
        self.dense4 = nn.Linear(512,3)
        self.relu = nn.ReLU()
        # self.dense1 = nn.Linear(63,50)
        # self.batch_norm1 = nn.BatchNorm1d(50)
        # self.dense2 = nn.Linear(50,30)
        # self.batch_norm2 = nn.BatchNorm1d(30)
        # self.dense3 = nn.BatchNorm1d(30, 3)
        # self.relu = nn.ReLU()

    def forward(self,x):
        x = self.dropout1(self.batch_norm1(self.relu(self.dense1(x))))
        x = self.dropout2(self.batch_norm2(self.relu(self.dense2(x))))
        x = self.dropout3(self.batch_norm3(self.relu(self.dense3(x))))
        return self.dense4(x)