tf.lite.TFLiteConverter     View source on GitHub    Converts a TensorFlow model into TensorFlow Lite model. 
tf.lite.TFLiteConverter(
    funcs, trackable_obj=None
)
 Example usage: # Converting a SavedModel to a TensorFlow Lite model.
converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
tflite_model = converter.convert()

# Converting a tf.Keras model to a TensorFlow Lite model.
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()

# Converting ConcreteFunctions to a TensorFlow Lite model.
converter = tf.lite.TFLiteConverter.from_concrete_functions([func])
tflite_model = converter.convert()

 


 Args
  funcs   List of TensorFlow ConcreteFunctions. The list should not contain duplicate elements.  
  trackable_obj   tf.AutoTrackable object associated with funcs. A reference to this object needs to be maintained so that Variables do not get garbage collected since functions have a weak reference to Variables. This is only required when the tf.AutoTrackable object is not maintained by the user (e.g. from_saved_model).   
 


 Attributes
  allow_custom_ops   Boolean indicating whether to allow custom operations. When False, any unknown operation is an error. When True, custom ops are created for any op that is unknown. The developer needs to provide these to the TensorFlow Lite runtime with a custom resolver. (default False)  
  optimizations   Experimental flag, subject to change. A list of optimizations to apply when converting the model. E.g. [Optimize.DEFAULT]  
  representative_dataset   A representative dataset that can be used to generate input and output samples for the model. The converter can use the dataset to evaluate different optimizations. Note that this is an optional attribute but it is necessary if INT8 is the only support builtin ops in target ops.  
  target_spec   Experimental flag, subject to change. Specification of target device.  
  inference_input_type   Data type of the input layer. Note that integer types (tf.int8 and tf.uint8) are currently only supported for post training integer quantization and quantization aware training. (default tf.float32, must be in {tf.float32, tf.int8, tf.uint8})  
  inference_output_type   Data type of the output layer. Note that integer types (tf.int8 and tf.uint8) are currently only supported for post training integer quantization and quantization aware training. (default tf.float32, must be in {tf.float32, tf.int8, tf.uint8})  
  experimental_new_converter   Experimental flag, subject to change. Enables MLIR-based conversion instead of TOCO conversion. (default True)    Methods convert View source 
convert()
 Converts a TensorFlow GraphDef based on instance variables.
 


 Returns   The converted data in serialized format.  

 


 Raises
  ValueError   No concrete functions is specified. Multiple concrete functions are specified. Input shape is not specified. Invalid quantization parameters.    from_concrete_functions View source 
@classmethod
from_concrete_functions(
    funcs
)
 Creates a TFLiteConverter object from ConcreteFunctions.
 


 Args
  funcs   List of TensorFlow ConcreteFunctions. The list should not contain duplicate elements. Currently converter can only convert a single ConcreteFunction. Converting multiple functions is under development.   
 


 Returns   TFLiteConverter object.  

 


 Raises   Invalid input type.  
 from_keras_model View source 
@classmethod
from_keras_model(
    model
)
 Creates a TFLiteConverter object from a Keras model.
 


 Args
  model   tf.Keras.Model   
 


 Returns   TFLiteConverter object.  
 from_saved_model View source 
@classmethod
from_saved_model(
    saved_model_dir, signature_keys=None, tags=None
)
 Creates a TFLiteConverter object from a SavedModel directory.
 


 Args
  saved_model_dir   SavedModel directory to convert.  
  signature_keys   List of keys identifying SignatureDef containing inputs and outputs. Elements should not be duplicated. By default the signatures attribute of the MetaGraphdef is used. (default saved_model.signatures)  
  tags   Set of tags identifying the MetaGraphDef within the SavedModel to analyze. All tags in the tag set must be present. (default set(SERVING))   
 


 Returns   TFLiteConverter object.  

 


 Raises   Invalid signature keys.