paddle转换为tflite

PaddlePaddle模型转换为TensorFlow Lite模型的步骤如下：

1. 安装PaddlePaddle和TensorFlow Lite：

pip install paddlepaddle
pip install tensorflow==2.5.0 tensorflow-gpu==2.5.0
pip install tflite-support==0.1.0rc4

2. 将PaddlePaddle模型转换为TensorFlow模型：

import paddle
import paddle.nn.functional as F
import tensorflow as tf

paddle_model = paddle.Model(MyModel())
paddle_model.load('model.pdparams')

# Define a converter
converter = paddle2tf.Converter()

# Convert the PaddlePaddle model to TensorFlow
tf_model = converter(paddle_model, input_spec=[(1, 3, 224, 224)], target_dir='tf_model')

3. 将TensorFlow模型转换为TensorFlow Lite模型：

import tensorflow as tf
from tensorflow.python.platform import gfile

# Load the TensorFlow model
with tf.Graph().as_default() as graph:
    with tf.compat.v1.Session() as sess:
        with gfile.FastGFile('tf_model.pb', 'rb') as f:
            graph_def = tf.compat.v1.GraphDef()
            graph_def.ParseFromString(f.read())
            tf.import_graph_def(graph_def, name='')

# Convert the TensorFlow model to TensorFlow Lite
converter = tf.compat.v1.lite.TFLiteConverter.from_session(sess, [input_tensor], [output_tensor])
converter.target_ops = [tf.compat.v1.lite.OpsSet.TFLITE_BUILTINS, tf.compat.v1.lite.OpsSet.SELECT_TF_OPS]
tflite_model = converter.convert()

# Save the TensorFlow Lite model
with open('model.tflite', 'wb') as f:
    f.write(tflite_model)

以上就是将PaddlePaddle模型转换为TensorFlow Lite模型的步骤。注意，这个过程可能会因为模型的复杂度和大小而需要较长时间。