Difference between revisions of "Converting to TensorFlow Lite"

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** [[TensorFlow Lite converter]]
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{{#seo:
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|title=PRIMO.ai
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|titlemode=append
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|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
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}}
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[https://www.youtube.com/results?search_query=tensorflow+lite+convert+lite.TFLiteConverter+artificial+intelligence+deep+learning Youtube search...] 
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[https://www.google.com/search?q=tensorflow+lite+lite.TFLiteConverter+machine+learning+convert+ML+artificial+intelligence ...Google search]
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* [[TensorFlow]]
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* [[TensorFlow Lite]]
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* [[Watch me Build a Healthcare Startup]]
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== TensorFlow Lite converter: lite.TFLiteConverter ==
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* [https://www.tensorflow.org/api_docs/python/tf/lite/TFLiteConverter lite.TFLiteConverter | TensorFlow]
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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.
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# Converting a GraphDef from session.
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converter = lite.TFLiteConverter.from_session(sess, in_tensors, out_tensors)
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tflite_model = converter.convert()
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open("converted_model.tflite", "wb").write(tflite_model)
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# Converting a GraphDef from file.
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converter = lite.TFLiteConverter.from_frozen_graph(
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  graph_def_file, input_arrays, output_arrays)
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tflite_model = converter.convert()
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open("converted_model.tflite", "wb").write(tflite_model)
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# Converting a SavedModel.
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converter = lite.TFLiteConverter.from_saved_model(saved_model_dir)
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tflite_model = converter.convert()
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# Converting a tf.keras model.
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converter = lite.TFLiteConverter.from_keras_model_file(keras_model)
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tflite_model = converter.convert()
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<youtube>ICY4Lvhyobk</youtube>
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== TocoConverter (THIS FUNCTION IS DEPRECATED) ==
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* [[Colaboratory]]
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<youtube>MZx1fhbL2q4</youtube>
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<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)