Difference between revisions of "Converting to TensorFlow Lite"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=tensorflow+lite+convert+lite.TFLiteConverter+artificial+intelligence+deep+learning Youtube search...] |
| − | [ | + | [https://www.google.com/search?q=tensorflow+lite+lite.TFLiteConverter+machine+learning+convert+ML+artificial+intelligence ...Google search] |
| − | |||
* [[TensorFlow]] | * [[TensorFlow]] | ||
* [[TensorFlow Lite]] | * [[TensorFlow Lite]] | ||
| + | * [[Watch me Build a Healthcare Startup]] | ||
| − | The TensorFlow Lite converter is used to convert TensorFlow models into an optimized FlatBuffer format, so that they can be used by the TensorFlow Lite interpreter. | + | == TensorFlow Lite converter: lite.TFLiteConverter == |
| + | * [https://www.tensorflow.org/api_docs/python/tf/lite/TFLiteConverter lite.TFLiteConverter | TensorFlow] | ||
| + | The TensorFlow Lite converter is used to convert TensorFlow models; GraphDef or SavedModel into an optimized FlatBuffer format, so that they can be used by the TensorFlow Lite interpreter or graph visualization. | ||
| + | |||
| + | # Converting a GraphDef from session. | ||
| + | converter = lite.TFLiteConverter.from_session(sess, in_tensors, out_tensors) | ||
| + | tflite_model = converter.convert() | ||
| + | open("converted_model.tflite", "wb").write(tflite_model) | ||
| + | |||
| + | # Converting a GraphDef from file. | ||
| + | converter = lite.TFLiteConverter.from_frozen_graph( | ||
| + | graph_def_file, input_arrays, output_arrays) | ||
| + | tflite_model = converter.convert() | ||
| + | open("converted_model.tflite", "wb").write(tflite_model) | ||
| + | |||
| + | # Converting a SavedModel. | ||
| + | converter = lite.TFLiteConverter.from_saved_model(saved_model_dir) | ||
| + | tflite_model = converter.convert() | ||
| + | |||
| + | # Converting a tf.keras model. | ||
| + | converter = lite.TFLiteConverter.from_keras_model_file(keras_model) | ||
| + | tflite_model = converter.convert() | ||
<youtube>ICY4Lvhyobk</youtube> | <youtube>ICY4Lvhyobk</youtube> | ||
| + | |||
| + | |||
| + | == TocoConverter (THIS FUNCTION IS DEPRECATED) == | ||
| + | * [[Colaboratory]] | ||
| + | <youtube>MZx1fhbL2q4</youtube> | ||
| + | <youtube>cWrb3qIFlCQ</youtube> | ||
Latest revision as of 06:31, 28 March 2023
Youtube search... ...Google search
TensorFlow Lite converter: lite.TFLiteConverter
The TensorFlow Lite converter is used to convert TensorFlow models; GraphDef or SavedModel into an optimized FlatBuffer format, so that they can be used by the TensorFlow Lite interpreter or graph visualization.
# Converting a GraphDef from session.
converter = lite.TFLiteConverter.from_session(sess, in_tensors, out_tensors)
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)
# Converting a GraphDef from file.
converter = lite.TFLiteConverter.from_frozen_graph(
graph_def_file, input_arrays, output_arrays)
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)
# Converting a SavedModel. converter = lite.TFLiteConverter.from_saved_model(saved_model_dir) tflite_model = converter.convert()
# Converting a tf.keras model. converter = lite.TFLiteConverter.from_keras_model_file(keras_model) tflite_model = converter.convert()
TocoConverter (THIS FUNCTION IS DEPRECATED)
