import torch
import torch.nn as nn


class Model(nn.Module):
    def __init__(self, beta=1.0, gamma=1.0):
        super().__init__()
        self.beta = beta
        self.gamma = gamma

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        # AHAF Formula: beta * x * sigmoid(gamma * x)
        return self.beta * x * torch.sigmoid(self.gamma * x)


batch_size = 1024
feature_dim = 1024


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


def get_init_inputs():
    return [1.0, 1.0]