class_docstr: Symbolic shape inference.
  Generates constraints over type variables.
  Currently all constraints are equality constraints.
class_docstr_tok: ["Symbolic","shape","inference",".","Generates","constraints","over","type","variables",".","Currently","all","constraints","are","equality","constraints","."]
docstr: Infers algebraic relations
code: def symbolic_relations(self):
      """
      Infers algebraic relations
      """
      graph = self.traced.graph
      for n in graph.nodes:
          self.infer_symbolic_relations(n)
      return True
  
imports: from functools import reduce
  import torch
  import operator
  from torch.fx.tensor_type import Dyn, is_consistent, TensorType, is_more_precise
  from typing import Callable, Dict
  from torch.fx.node import Target, Node
  from torch.nn.modules.batchnorm import BatchNorm2d
  from torch.nn.modules.conv import Conv2d
  from torch.fx.experimental.refinement_types import Equality
  import itertools
  from torch.fx.experimental.unification import Var
  import sympy
label_desc: Use image node_id 3 for calling the Refine obj's underlying member method code with example usage: obj.symbolic_relations() and returns: True