class_docstr: Tests PyTorch and Tensorflow model imports
docstr: Verifies shape inputs in reshape are properly imported
docstr_tok: ["Verifies","shape","inputs","in","reshape","are","properly","imported"]
code: def test_reshape_plain_text_conversion(self):
      """Verifies shape inputs in reshape are properly imported"""
  
      class Net(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.fc1 = torch.nn.Linear(4, 4)
  
          def forward(self, x):
              # (1, 4) is stored in a constant module
              out = x.reshape(1, 4)
              out = self.fc1(out)
              return out
  
      model = Net()
      x = torch.ones(2, 2)
      x_enc = crypten.cryptensor(x)
      y = model(x)
      model_crypten = onnx_converter.from_pytorch(
          model, torch.empty(x.shape)
      )
  
      model_crypten.encrypt()
      y_enc = model_crypten(x_enc)
      self.assertTrue(y_enc.shape == y.shape)
  
imports: import collections
  import io
  import logging
  import os
  import unittest
  import crypten
  import torch
  from crypten.common.tensor_types import is_float_tensor
  from crypten.config import cfg
  from crypten.nn import onnx_converter
  from test.multiprocess_test_case import get_random_test_tensor, MultiProcessTestCase, onehot
label_desc: Use image node_id 12 for calling the TestOnnxConverter obj's underlying member method code with example usage: obj.test_reshape_plain_text_conversion() and returns: out