PyTorch eager

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    A model that computes Smooth L1 (Huber) Loss for regression tasks.

    Parameters:
        None
    """
    def __init__(self):
        super(Model, self).__init__()

    def forward(self, predictions, targets):
        return torch.nn.functional.smooth_l1_loss(predictions, targets)

batch_size = 32768
input_shape = (32768,)
dim = 1

def get_inputs():
    scale = torch.rand(())
    return [torch.rand(batch_size, *input_shape)*scale, torch.rand(batch_size, *input_shape)]

def get_init_inputs():
    return []