class_docstr: Package of a program from :func:`export`. It contains
  an :class:`torch.fx.Graph` that represents Tensor computation, a state_dict containing
  tensor values of all lifted parameters and buffers, and various metadata.
  
  You can call an ExportedProgram like the original callable traced by
  :func:`export` with the same calling convention.
  
  To perform transformations on the graph, use ``.module`` property to access
  an :class:`torch.fx.GraphModule`. You can then use
  `FX transformation <https://pytorch.org/docs/stable/fx.html#writing-transformations>`_
  to rewrite the graph. Afterwards, you can simply use :func:`export`
  again to construct a correct ExportedProgram.
code: def _check_input_constraints(self, *args):
      from torch._export.utils import _check_input_constraints_for_graph
  
      placeholders = [
          p for p in self.graph.nodes if p.op == "placeholder"
      ]
      input_placeholders = [
          p
          for p, s in zip(
              placeholders, self.graph_signature.input_specs
          )
          if s.kind == InputKind.USER_INPUT
      ]
      _check_input_constraints_for_graph(
          input_placeholders, args, self.range_constraints
      )
  
imports: import copy
  import dataclasses
  import functools
  import types
  from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, Type, TYPE_CHECKING, Union
  import torch
  import torch.fx._pytree
  import torch.utils._pytree
  from torch.fx._compatibility import compatibility
  from torch.fx.experimental.proxy_tensor import maybe_disable_fake_tensor_mode
  from torch.fx.passes.infra.pass_base import PassResult
  from torch.fx.passes.infra.pass_manager import PassManager
  from .graph_signature import _sig_to_specs, ArgumentSpec, ConstantArgument, ExportGraphSignature, InputKind, InputSpec, OutputKind, OutputSpec, SymIntArgument, TensorArgument
label_desc: Use image node_id 22 for calling the ExportedProgram obj's underlying member method code with example usage: obj._check_input_constraints() without return types