Fix an issue where multiple instances of DefaultNBitQuantizeRegistry could interfere with each other's configuration.

PiperOrigin-RevId: 931228650

Author: ratgr

tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/BUILD

@@ -64,13 +64,13 @@ py_library(
     ],
     # strict_deps = True,
     deps = [
+        ":default_n_bit_quantize_configs",
+        ":default_n_bit_quantizers",
         # tensorflow dep1,
         "//tensorflow_model_optimization/python/core/keras:compat",
         "//tensorflow_model_optimization/python/core/quantization/keras:quantize_config",
         "//tensorflow_model_optimization/python/core/quantization/keras:quantize_registry",
         "//tensorflow_model_optimization/python/core/quantization/keras:quantizers",
-        "//tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit:default_n_bit_quantize_configs",
-        "//tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit:default_n_bit_quantizers",
     ],
 )
 

tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/default_n_bit_quantize_registry.py

@@ -185,9 +185,15 @@ def __init__(self, disable_per_axis=False,
     self._num_bits_activation = num_bits_activation
     self._layer_quantize_map = {}
     for quantize_info in self._LAYER_QUANTIZE_INFO:
-      quantize_info.num_bits_weight = num_bits_weight
-      quantize_info.num_bits_activation = num_bits_activation
-      self._layer_quantize_map[quantize_info.layer_type] = quantize_info
+      new_quantize_info = _QuantizeInfo(
+          layer_type=quantize_info.layer_type,
+          weight_attrs=quantize_info.weight_attrs,
+          activation_attrs=quantize_info.activation_attrs,
+          quantize_output=quantize_info.quantize_output,
+          num_bits_weight=num_bits_weight,
+          num_bits_activation=num_bits_activation,
+      )
+      self._layer_quantize_map[new_quantize_info.layer_type] = new_quantize_info
 
     # Hack for `Activation` layer. That is the only layer with a separate
     # QuantizeConfig.