code: def quantize_tensorflow(
      model: tf.Module,
      quantization_type: QuantizationType,
      input_data_tensorflow: List[Tuple[tf.Tensor, ...]],
  ):
      if quantization_type is QuantizationType.DYNAMIC:
          quantized_model = _quantize_dynamic(model)
      elif quantization_type is QuantizationType.STATIC:
          quantized_model = _quantize_static(
              model, input_data_tensorflow
          )
      elif quantization_type is QuantizationType.HALF:
          quantized_model = _half_precision(model)
      else:
          raise NotImplementedError(
              f"Quantization not supported for type {quantization_type}"
          )
  
      return quantized_model
  
imports: from typing import List, Tuple
  from nebullvm.core.models import QuantizationType
  from nebullvm.optional_modules.tensorflow import tensorflow
label_desc: Use image node_id 4 for calling a global function with example usage: quantize_tensorflow(model, quantization_type, input_data_tensorflow) and returns: quantized_model