class_docstr: Module that never leaves evaluation mode.
class_docstr_tok: ["Module","that","never","leaves","evaluation","mode","."]
docstr: Force network to always be in evaluation mode.
docstr_tok: ["Force","network","to","always","be","in","evaluation","mode","."]
code: def train(self, mode: bool) -> "NoTrainInceptionV3":
      """Force network to always be in evaluation mode."""
      return super().train(False)
  
imports: from copy import deepcopy
  from typing import Any, List, Optional, Sequence, Tuple, Union
  import torch
  from torch import Tensor
  from torch.nn import Module
  from torch.nn.functional import adaptive_avg_pool2d
  from torchmetrics.metric import Metric
  from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCH_FIDELITY_AVAILABLE
  from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
label_desc: Use image node_id 2 for calling the NoTrainInceptionV3 obj's underlying member method code with example usage: obj.train(mode) and returns: super