class_docstr: QuantizeConfig that quantizes output with fixed range.
class_docstr_tok: ["QuantizeConfig","that","quantizes","output","with","fixed","range","."]
code: def __init__(
      self, config, num_bits, init_min, init_max, narrow_range
  ):
      self.config = config
      self.num_bits = num_bits
      self.init_min = init_min
      self.init_max = init_max
      self.narrow_range = narrow_range
      self.fixed_quantizer = quantizers.FixedQuantizer(
          num_bits=num_bits,
          init_min=init_min,
          init_max=init_max,
          narrow_range=narrow_range,
      )
  
imports: import abc
  import six
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras import utils
label_desc: Use image node_id 1 to create a new FixedQuantizeConfig object from inherited base classes: QuantizeConfig with example: obj = FixedQuantizeConfig(config, num_bits, init_min, init_max, narrow_range)