code: def __init__(
      self,
      diagnostic_context: diagnostics.DiagnosticContext,
      module: torch.fx.GraphModule,
      decomposition_table: Mapping[torch._ops.OpOverload, Callable],
      enable_dynamic_axes: bool,
      allow_fake_constant: Optional[bool] = False,
  ):
      super().__init__(diagnostic_context, module)
      self.decomposition_table = decomposition_table
      self.enable_dynamic_axes = enable_dynamic_axes
      self.allow_fake_constant = allow_fake_constant
  
file_path: pytorch/torch/onnx/_internal/fx/passes/decomp.py
imports: from __future__ import annotations
  import contextlib
  from typing import Callable, Mapping, Optional
  import torch
  import torch._ops
  import torch.fx
  from torch._dispatch import python
  from torch._subclasses import fake_tensor
  from torch.fx.experimental import proxy_tensor
  from torch.onnx._internal import _beartype
  from torch.onnx._internal.fx import _pass, diagnostics
  from torch.onnx._internal.fx.passes import _utils
label_desc: Use image node_id 1 to create a new Decompose object from inherited base classes: _pass with example: obj = Decompose(diagnostic_context, module, decomposition_table, enable_dynamic_axes, allow_fake_constant)