class_docstr: coremltools internal representation of a torch IR node.
  Can construct itself from a provided torchIR node or manually constructed with
  args for testing.
  
  See InternalTorchIRGraph for the motivation behind this structure.
docstr: Arguments:
      name: Name of the node.
      kind: the kind (op) of the node.
      inputs: list of input symbols.
      outputs: list of output symbols.
      parent: The InternalTorchIRGraph/Block this node belongs to.
      attr:  dict of named attributes.
      blocks: list of InternalTorchIRBlock.
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code: def __init__(
      self,
      kind,
      inputs,
      outputs,
      name=None,
      parent=None,
      attr=None,
      blocks=None,
  ):
      """
      Arguments:
          name: Name of the node.
          kind: the kind (op) of the node.
          inputs: list of input symbols.
          outputs: list of output symbols.
          parent: The InternalTorchIRGraph/Block this node belongs to.
          attr:  dict of named attributes.
          blocks: list of InternalTorchIRBlock.
      """
      if not name and not outputs:
          self.name = ""
      else:
          self.name = name if name else outputs[0]
  
      self.kind = kind
      self.inputs = inputs
      self.outputs = outputs
      self.parent = parent
      self.attr = attr if attr is not None else {"value": None}
      self.blocks = blocks if blocks is not None else []
  
imports: from collections import OrderedDict
  import torch
  from torch.fx.node import Node
  from coremltools import _logger
  from .edgeir_utils import extract_inputs_from_edge_program
  from .torchscript_utils import _expand_and_optimize_ir
label_desc: Use image node_id 1 to create a new InternalTorchIRNode object  with example: obj = InternalTorchIRNode(kind, inputs, outputs, name, parent, attr, blocks)