convert_graph.py

import tensorflow as tf
from tensorflow import keras
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
import numpy as np


model = tf.keras.models.load_model('./checkpoints/yolov4-416_tiny/')
print(model.summary())
full_model = tf.function(lambda x: model(x))
full_model = full_model.get_concrete_function(
    tf.TensorSpec(model.inputs[0].shape, model.inputs[0].dtype))
frozen_func = convert_variables_to_constants_v2(full_model)
frozen_func.graph.as_graph_def()

layers = [op.name for op in frozen_func.graph.get_operations()]
print("-" * 60)
print("Frozen model layers: ")
for layer in layers:
    print(layer)
print("-" * 60)
print("Frozen model inputs: ")
print(frozen_func.inputs)
print("Frozen model outputs: ")
print(frozen_func.outputs)


tf.io.write_graph(graph_or_graph_def=frozen_func.graph,
                  logdir='./checkpoints/',
                  name='tf2_frozen_graph.pb',
                  as_text=False)

tf.io.write_graph(graph_or_graph_def=frozen_func.graph,
                  logdir='./checkpoints/',
                  name='tf2_frozen_graph.pbtxt',
                  as_text=True)