code: def forward(self, x: torch.Tensor) -> torch.Tensor:  # type: ignore
      out = self.fc1(x)
      out = self.relu1(out)
      out = self.fc2(out)
      out = self.relu2(out)
      out = self.fc3(out)
      out = self.sigmoid(out)
      out = self.identity(out)
      return out
  
imports: import logging
  import os
  from typing import Any, List, Tuple, Union
  import numpy
  import pytest
  from sklearn.datasets import make_blobs
  import torch
  from torch.cuda.amp.autocast_mode import autocast
  import torch.nn
  from torch.utils.data import DataLoader
  import torchvision
  import torchvision.transforms
  from fairscale.fair_dev.common_paths import DATASET_CACHE_ROOT
  from fairscale.fair_dev.testing.testing import skip_a_test_if_in_CI
  from fairscale.optim.layerwise_gradient_scaler import LayerwiseGradientScaler
label_desc: Use image node_id 2 for calling the FeedForward obj's underlying member method code with example usage: obj.forward(x) and returns: out