Add tanh as supported activation in QAT

PiperOrigin-RevId: 377211156

Author: Xhark

tensorflow_model_optimization/python/core/quantization/keras/default_8bit/default_8bit_quantize_registry.py

@@ -489,7 +489,7 @@ def get_output_quantizers(self, layer):
       # 'relu' should generally get fused into the previous layer.
       return [quantizers.MovingAverageQuantizer(
           num_bits=8, per_axis=False, symmetric=False, narrow_range=False)]
-    elif layer.activation.__name__ in ['linear', 'softmax', 'sigmoid']:
+    elif layer.activation.__name__ in ['linear', 'softmax', 'sigmoid', 'tanh']:
       return []
 
     raise ValueError('Activation {} not supported by '

tensorflow_model_optimization/python/core/quantization/keras/default_8bit/default_8bit_quantize_registry_test.py

@@ -476,7 +476,7 @@ def testRaisesErrorUnsupportedActivation(self):
     )
 
     with self.assertRaises(ValueError):
-      quantize_config.get_output_quantizers(keras.layers.Activation('tanh'))
+      quantize_config.get_output_quantizers(keras.layers.Activation('swish'))
 
     with self.assertRaises(ValueError):
       quantize_config.get_output_quantizers(

tensorflow_model_optimization/python/core/quantization/keras/quantize_aware_activation.py

@@ -77,7 +77,7 @@ class QuantizeAwareActivation(object):
   # on inclusion. Verify in TFLite before enabling.
 
   # These activations should be quantized prior to the activation being applied.
-  _PRE_QUANT_ACTIVATIONS = frozenset({'softmax', 'sigmoid'})
+  _PRE_QUANT_ACTIVATIONS = frozenset({'softmax', 'sigmoid', 'tanh'})
 
   # These activations should be quantized after the activation has been applied.
   _POST_QUANT_ACTIVATIONS = frozenset({'linear', 'relu'})