```python
import torch
import torch.nn as nn
import torch.nn.functional as F

class SSPBlock(nn.Module):
    def __init__(self, in_channels):
        super(SSPBlock, self).__init__()
        self.conv1 = nn.Conv2d(in_channels, in_channels // 2, 1, 1)
        self.conv2 = nn.Conv2d(in_channels // 2, in_channels, 3, 1, padding=1)
        self.conv3 = nn.Conv2d(in_channels, in_channels // 2, 1, 1)
        self.conv4 = nn.Conv2d(in_channels // 2, in_channels, 3, 1, padding=1)
        self.conv5 = nn.Conv2d(in_channels, in_channels // 2, 1, 1)
        self.conv6 = nn.Conv2d(in_channels // 2, in_channels, 3, 1, padding=1)
        self.pool = nn.MaxPool2d(5, 1, 2)

    def forward(self, x):
        conv1 = F.relu(self.conv1(x))
        conv2 = F.relu(self.conv2(conv1))
        conv3 = F.relu(self.conv3(conv2))
        conv4 = F.relu(self.conv4(conv3))
        conv5 = F.relu(self.conv5(conv4))
        conv6 = F.relu(self.conv6(conv5))
        pooled = self.pool(conv6)
        out = torch.cat((conv1, conv3, conv5, pooled), dim=1)
        return out
```
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence