class_docstr: A torch.Tensor input or an intermediate value in the FX graph
class_docstr_tok: ["A","torch.Tensor","input","or","an","intermediate","value","in","the","FX","graph"]
docstr: Get the actual value represented by this variable if computation is run
  using the user-provided inputs.
  NOTE: this runs actual tensor computation and may be
  slow and memory-intensive.
code: def get_real_value(self):
      """
      Get the actual value represented by this variable if computation is run
      using the user-provided inputs.
      NOTE: this runs actual tensor computation and may be
      slow and memory-intensive.
      """
      return get_real_value(self.proxy.node, self.proxy.tracer)
  
imports: import functools
  import inspect
  import operator
  import types
  from typing import Dict, List
  import sympy
  import torch._numpy
  import torch.fx
  import torch.random
  from torch._dynamo import compiled_autograd
  from torch.fx.experimental.symbolic_shapes import guard_scalar, GuardOnDataDependentSymNode, has_free_symbols, is_symbolic, SymTypes
  from ..None import config, variables
  from .._trace_wrapped_higher_order_op import trace_wrapped
  from ..exc import unimplemented, UserError, UserErrorType
  from ..guards import GuardBuilder, install_guard
  from ..source import AttrSource
  from ..utils import fqn, get_custom_getattr, get_fake_value, get_real_value, guard_if_dyn, object_has_getattribute, product, proxy_args_kwargs, tensortype_to_dtype
  from .base import VariableTracker
  from .constant import ConstantVariable
  from .lists import SizeVariable
label_desc: Use image node_id 1 for calling the TensorVariable obj's underlying member method code with example usage: obj.get_real_value() and returns: get_real_value