Removed Optimization TFLite flag from quantize.py

Removed the TFLite Optimization flag for the FP32 tflite version, as it produced a Hybrid model (both INT8 and FP32 operations), which is not supported by TFLM.

benchmark/training/keyword_spotting/quantize.py

@@ -12,7 +12,6 @@
   print(f"Converting trained model {Flags.saved_model_path} to TFL model at {Flags.tfl_file_name}")
   model = tf.keras.models.load_model(Flags.saved_model_path)
   converter = tf.lite.TFLiteConverter.from_keras_model(model)
-  converter.optimizations = [tf.lite.Optimize.DEFAULT]
 
   fp32_tfl_file_name = Flags.tfl_file_name[:Flags.tfl_file_name.rfind('.')] + '_float32.tflite'
   tflite_float_model = converter.convert()