5 – تحويل ONNX إلى TensorFlow – سلسلة مصغرة

Welcome to the fifth installment of our Mini-Series on converting ONNX models to TensorFlow in Arabic. In this tutorial, we will cover the process of converting an ONNX model to TensorFlow. Let’s get started!

Step 1: Install the required libraries

Before we begin, make sure you have the necessary libraries installed. You will need ONNX and TensorFlow. You can install them using the following commands:

For ONNX:

pip install onnx

For TensorFlow:

pip install tensorflow

Step 2: Load the ONNX model

Next, you need to load the ONNX model that you want to convert to TensorFlow. You can do this using the following code:

<code>
import onnx
from onnx_tf.backend import prepare

onnx_model = onnx.load('your_model.onnx')
tf_rep = prepare(onnx_model)
</code>

This code will load the ONNX model and prepare it for conversion to TensorFlow.

Step 3: Convert the ONNX model to TensorFlow

Now that you have loaded the ONNX model, you can convert it to TensorFlow using the following code:

<code>
tf_rep.export_graph('your_model.pb')
</code>

This code will convert the ONNX model to TensorFlow and save the resulting TensorFlow graph in a .pb file.

Step 4: Load the TensorFlow model

Once you have converted the ONNX model to TensorFlow, you can load the TensorFlow model using the following code:

<code>
import tensorflow as tf

tf_model = tf.GraphDef()
with open('your_model.pb', 'rb') as f:
    tf_model.ParseFromString(f.read())
</code>

This code will load the TensorFlow model from the .pb file.

Step 5: Run inference with the TensorFlow model

Finally, you can run inference with the TensorFlow model using the following code:

<code>
with tf.Session() as sess:
    outputs = sess.run(['output_name:0'], feed_dict={'input_name:0': input_data})
</code>

This code will run inference with the TensorFlow model using the input data and retrieve the outputs.

Congratulations! You have successfully converted an ONNX model to TensorFlow. Stay tuned for more tutorials in our Mini-Series on converting ONNX models to TensorFlow in Arabic.