code: def is_var_constraint_satisifed(pattern):
      # input must be rank 4
      if pattern.root_var.rank != 4:
          return False
      # output must be rank 4
      if pattern.out_op.outputs[0].rank != 4:
          return False
      if not (
          _check_var_scalar_value(pattern.neg.y, -1)
          or _check_var_scalar_value(pattern.neg.x, -1)
      ):
          return False
      if pattern.alpha_mul.x.val is not None:
          alpha = pattern.alpha_mul.x.val
      elif pattern.alpha_mul.y.val is not None:
          alpha = pattern.alpha_mul.y.val
      else:
          return False
      # alpha must be of shape (1, C, 1, 1) or (C, 1, 1)
      if len(alpha.shape) not in (3, 4):
          return False
      if alpha.size != alpha.shape[-3]:
          return False
  
      return True
  
imports: import numpy
  from coremltools.converters.mil.experimental.passes.generic_pass_infrastructure import fuse_all_blocks
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import get_new_symbol
  from coremltools.converters.mil.mil.passes.graph_pass import AbstractGraphPass
  from coremltools.converters.mil.mil.passes.helper import _check_child_op_type, _check_var_scalar_value, _check_var_scalar_value_in_interval, block_context_manager
  from coremltools.converters.mil.mil.passes.pass_registry import register_pass
label_desc: Use image node_id 1 for calling the FusePreluPattern1 obj's underlying member method code with example usage: obj.is_var_constraint_satisifed(pattern) and returns: True, False, False, False, False, False, False