code: def quantize_per_channel(context, node):
      input, scale, zero_point, axis, torch_dtype = _get_inputs(
          context, node, expected=[5]
      )
  
      if axis.val is None:
          raise ValueError(
              "quantization axis must be const at compile time"
          )
  
      _quantize_general(
          context, node, input, scale, zero_point, torch_dtype, axis.val
      )
  
imports: import numpy
  import torch
  from coremltools import _logger
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import Var, types
  from .ops import NUM_TO_TORCH_DTYPE, _create_linear_layer, _get_inputs, promote_input_dtypes
  from .torch_op_registry import register_torch_op
label_desc: Use image node_id 3 for calling a global function with example usage: quantize_per_channel(context, node) without return types