tensorflow - 将保存的 tensorflow 模型转换为 tensorflow Lite 的正确方法是什么

Question

我有一个与 model zoo 中的所有模型相同的已保存 tensorflow 模型.
我想将其转换为 tesorflow lite，我从 tensorflow github 中找到了以下方法(我的 tensorflw 版本是 2):

!wget http://download.tensorflow.org/models/object_detection/tf2/20200711/ssd_resnet50_v1_fpn_640x640_coco17_tpu-8.tar.gz 
# extract the downloaded file
!tar -xzvf ssd_resnet50_v1_fpn_640x640_coco17_tpu-8.tar.gz
    

!pip install tf-nightly
import tensorflow as tf
converter = tf.lite.TFLiteConverter.from_saved_model('ssd_mobilenet_v2_320x320_coco17_tpu-8/saved_model')
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.experimental_new_converter = True

converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]
tflite_model = converter.convert()

open("m.tflite", "wb").write(tflite_model)

但是转换模型的输出和输入形状与原始模型不匹配，请检查以下内容:

原始模型输入和输出形状

转换后的模型输入和输出形状

所以这里有问题!输入/输出形状应该与原始模型相匹配!
任何的想法？

Answer 1

从 Tensorflow github 问题，我使用他们的答案来解决我的问题。
Link
他们的做法:

!pip install tf-nightly
import tensorflow as tf

## TFLite Conversion
model = tf.saved_model.load("saved_model")
concrete_func = model.signatures[tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
concrete_func.inputs[0].set_shape([1, 300, 300, 3])
tf.saved_model.save(model, "saved_model_updated", signatures={"serving_default":concrete_func})
converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir='saved_model_updated', signature_keys=['serving_default'])

converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]
tflite_model = converter.convert()

## TFLite Interpreter to check input shape
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
input_shape = input_details[0]['shape']
print(input_shape)

[ 1 300 300 3]

谢谢 MeghnaNatraj