Update Quantizer params to match new scheme.

Quantizer params now match the defaults for the new
quantization spec at
https://www.tensorflow.org/lite/performance/quantization_spec

Note that this does not include special case handling
of per axis operations.

PiperOrigin-RevId: 278751220

Author: nutsiepully

tensorflow_model_optimization/python/core/quantization/keras/layers/conv_batchnorm.py

@@ -261,7 +261,7 @@ def __init__(
     if self.is_quantized:
       # TODO(b/142132535): update when we move to new quantization scheme.
       self.weight_quantizer = quantizers.LastValueQuantizer(
-          num_bits=8, per_axis=False, symmetric=False, narrow_range=True)
+          num_bits=8, per_axis=False, symmetric=True, narrow_range=True)
 
       self.activation_quantizer = quantizers.MovingAverageQuantizer(
           num_bits=8, per_axis=False, symmetric=False, narrow_range=False)
@@ -444,7 +444,7 @@ def __init__(
     self.is_quantized = is_quantized
     if self.is_quantized:
       self.weight_quantizer = quantizers.LastValueQuantizer(
-          num_bits=8, per_axis=False, symmetric=False, narrow_range=True)
+          num_bits=8, per_axis=False, symmetric=True, narrow_range=True)
 
       self.activation_quantizer = quantizers.MovingAverageQuantizer(
           num_bits=8, per_axis=False, symmetric=False, narrow_range=False)

tensorflow_model_optimization/python/core/quantization/keras/tflite/tflite_quantize_registry.py

@@ -261,7 +261,7 @@ def __init__(self, weight_attrs, activation_attrs, quantize_output):
     self.weight_quantizer = quantizers.LastValueQuantizer(
         num_bits=8, per_axis=False, symmetric=True, narrow_range=True)
     self.activation_quantizer = quantizers.MovingAverageQuantizer(
-        num_bits=8, per_axis=False, symmetric=True, narrow_range=False)
+        num_bits=8, per_axis=False, symmetric=False, narrow_range=False)
 
   def get_weights_and_quantizers(self, layer):
     return [(getattr(layer, weight_attr), self.weight_quantizer)