import torch
import torch.nn as nn


class Model(nn.Module):
    def __init__(self, threshold=0.0):
        super().__init__()
        self.threshold = threshold

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        return torch.where(x >= self.threshold, 1.0, -1.0)


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 [0.0]