PyTorch eager

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    Simple model that performs a matrix multiplication, applies Swish activation, and scales the result.
    """
    def __init__(self, in_features, out_features, scaling_factor):
        super(Model, self).__init__()
        self.matmul = nn.Linear(in_features, out_features)
        self.scaling_factor = scaling_factor

    def forward(self, x):
        x = self.matmul(x)
        x = x * torch.sigmoid(x)  # Swish activation
        x = x * self.scaling_factor
        return x

batch_size = 128
in_features = 32768
out_features = 32768
scaling_factor = 2.0

def get_inputs():
    return [torch.rand(batch_size, in_features)]

def get_init_inputs():
    return [in_features, out_features, scaling_factor]