import torch
import torch.nn as nn


class Model(nn.Module):
    def __init__(self, T=6.0):
        super().__init__()
        self.T = T

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        swish_val = x * torch.sigmoid(x)
        return torch.clamp(swish_val, -self.T, self.T)


batch_size = 128
feature_dim = 512


def get_inputs():
    x = torch.randn(batch_size, feature_dim, dtype=torch.float32)
    return [x]


def get_init_inputs():
    return [6.0]