code: def test_mse_loss(
      preds: torch.Tensor, target: torch.Tensor, output: torch.Tensor
  ):
      loss = loss_modules.MSELoss(MSELossConfig())
      assert loss(preds, target) == output
  
imports: import contextlib
  from typing import Optional, Type, Union
  import pytest
  import torch
  from marshmallow import ValidationError
  from ludwig.features.category_feature import CategoryOutputFeature
  from ludwig.features.set_feature import SetOutputFeature
  from ludwig.features.text_feature import TextOutputFeature
  from ludwig.modules import loss_modules
  from ludwig.schema.features.loss.loss import BWCEWLossConfig, CORNLossConfig, HuberLossConfig, MAELossConfig, MAPELossConfig, MSELossConfig, RMSELossConfig, RMSPELossConfig, SigmoidCrossEntropyLossConfig, SoftmaxCrossEntropyLossConfig
  from ludwig.schema.model_config import ModelConfig
  from tests.integration_tests.utils import category_feature, set_feature, text_feature
label_desc: Use image node_id 2 for calling a global function with example usage: test_mse_loss(preds, target, output) without return types