remove tflite part

Signed-off-by: xavier dupré <[email protected]>

Author: sdpython

examples/end2end_tfhub.py

@@ -73,43 +73,3 @@
                            number=10, globals=globals()))
 print('ort:', timeit.timeit("session.run(None, {'input_1:0': input})",
                             number=10, globals=globals()))
-
-########################################
-# Freezes the graph with tensorflow.lite.
-converter = tf.lite.TFLiteConverter.from_saved_model("efficientnetb0clas")
-tflite_model = converter.convert()
-with open("efficientnetb0clas.tflite", "wb") as f:
-    f.write(tflite_model)
-
-# Builds an interpreter.
-interpreter = tf.lite.Interpreter(model_path='efficientnetb0clas.tflite')
-interpreter.allocate_tensors()
-input_details = interpreter.get_input_details()
-output_details = interpreter.get_output_details()
-print("input_details", input_details)
-print("output_details", output_details)
-index = input_details[0]['index']
-
-
-def tflite_predict(input, interpreter=interpreter, index=index):
-    res = []
-    for i in range(input.shape[0]):
-        interpreter.set_tensor(index, input[i:i + 1])
-        interpreter.invoke()
-        res.append(interpreter.get_tensor(output_details[0]['index']))
-    return np.vstack(res)
-
-
-print(input[0:1].shape, "----", input_details[0]['shape'])
-output_data = tflite_predict(input, interpreter, index)
-print(output_data)
-
-########################################
-# Measures processing time again.
-
-print('tf:', timeit.timeit('model.predict(input)',
-                           number=10, globals=globals()))
-print('ort:', timeit.timeit("session.run(None, {'input_1:0': input})",
-                            number=10, globals=globals()))
-print('tflite:', timeit.timeit('tflite_predict(input)',
-                               number=10, globals=globals()))

examples/end2end_tfkeras.py

@@ -68,52 +68,3 @@
                            number=100, globals=globals()))
 print('ort:', timeit.timeit("session.run(None, {'input_1:0': input})",
                             number=100, globals=globals()))
-
-########################################
-# Freezes the graph with tensorflow.lite.
-converter = tf.lite.TFLiteConverter.from_saved_model("simple_rnn")
-tflite_model = converter.convert()
-with open("simple_rnn.tflite", "wb") as f:
-    f.write(tflite_model)
-
-# Builds an interpreter.
-interpreter = tf.lite.Interpreter(model_path='simple_rnn.tflite')
-interpreter.allocate_tensors()
-input_details = interpreter.get_input_details()
-output_details = interpreter.get_output_details()
-print("input_details", input_details)
-print("output_details", output_details)
-index = input_details[0]['index']
-
-
-def tflite_predict(input, interpreter=interpreter, index=index):
-    res = []
-    for i in range(input.shape[0]):
-        interpreter.set_tensor(index, input[i:i + 1])
-        interpreter.invoke()
-        res.append(interpreter.get_tensor(output_details[0]['index']))
-    return np.vstack(res)
-
-
-print(input[0:1].shape, "----", input_details[0]['shape'])
-output_data = tflite_predict(input, interpreter, index)
-print(output_data)
-
-########################################
-# Measures processing time again.
-
-print('tf:', timeit.timeit('model.predict(input)',
-                           number=100, globals=globals()))
-print('ort:', timeit.timeit("session.run(None, {'input_1:0': input})",
-                            number=100, globals=globals()))
-print('tflite:', timeit.timeit('tflite_predict(input)',
-                               number=100, globals=globals()))
-
-########################################
-# Measures processing time only between onnxruntime and
-# tensorflow lite with more loops.
-
-print('ort:', timeit.timeit("session.run(None, {'input_1:0': input})",
-                            number=10000, globals=globals()))
-print('tflite:', timeit.timeit('tflite_predict(input)',
-                               number=10000, globals=globals()))