class_docstr: Module that never leaves evaluation mode.
class_docstr_tok: ["Module","that","never","leaves","evaluation","mode","."]
docstr: Forward pass of neural network with reshaping of output.
docstr_tok: ["Forward","pass","of","neural","network","with","reshaping","of","output","."]
code: def forward(self, x: Tensor) -> Tensor:
      """Forward pass of neural network with reshaping of output."""
      out = self._torch_fidelity_forward(x)
      return out[0].reshape(x.shape[0], -1)
  
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 4 for calling the NoTrainInceptionV3 obj's underlying member method code with example usage: obj.forward(x) and returns: out