class_docstr: An error-collecting object which supports error recovery.
  
  It is intended to be used like a context manager:
  
  >>> with Errors("Top-level error message") as errs:
  >>>     ...
class_docstr_tok: ["An","error-collecting","object","which","supports","error","recovery",".","It","is","intended","to","be","used","like","a","context","manager",":",">",">",">","with","Errors","(","``","Top-level","error","message","''",")","as","errs",":",">",">",">","..."]
docstr: If there are any errors in the error context, short-circuit.
  
  This is used to prevent error cascades.
docstr_tok: ["If","there","are","any","errors","in","the","error","context",",","short-circuit",".","This","is","used","to","prevent","error","cascades","."]
code: def failIfErrs(self):
      """
      If there are any errors in the error context, short-circuit.
  
      This is used to prevent error cascades.
      """
      if self.errors:
          self.fail()
  
imports: import difflib
  import io
  import numpy
  import onnx
  import onnx.helper
  import torch
  import torch.jit
  import torch.onnx
label_desc: Use image node_id 13 for calling the Errors obj's underlying member method code with example usage: obj.failIfErrs() without return types