PyTorch eager

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    Simple model that finds the index of the minimum value along a specified dimension.
    """
    def __init__(self, dim: int):
        """
        Initializes the model with the dimension to perform argmin on.

        Args:
            dim (int): Dimension along which to find the minimum value.
        """
        super(Model, self).__init__()
        self.dim = dim

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        """
        Finds the index of the minimum value along the specified dimension.

        Args:
            x (torch.Tensor): Input tensor.

        Returns:
            torch.Tensor: Tensor containing the indices of the minimum values along the specified dimension.
        """
        return torch.argmin(x, dim=self.dim)

batch_size = 128
dim1 = 4096
dim2 = 4095
dim = 1

def get_inputs():
    x = torch.rand(batch_size, dim1, dim2)
    return [x]

def get_init_inputs():
    return [dim]