How do I load a TensorFlow PB model?

readme.md

1. Load a pb file into tensorflow as a graph.
2. Use the loaded graph as the default graph.
3. Generate tf records (some binary data format)
4. Save the loaded graph in tensorboard and then visualize it.
5. Do inference with loaded graph.
6. Feed image data into predictive model.
7. Feed data from tf records into predictive model.

What is PB file in TensorFlow?

pb stands for protobuf. In TensorFlow, the protbuf file contains the graph definition as well as the weights of the model. Thus, a pb file is all you need to be able to run a given trained model. Given a pb file, you can load it as follow.

How do I restore a saved model in TensorFlow?

You can also take this easier way.

1. Step 1: initialize all your variables. W1 = tf.
2. Step 2: save the session inside model Saver and save it. model_saver = tf.train.Saver() # Train the model and save it in the end model_saver.save(session, “saved_models/CNN_New.ckpt”)
3. Step 3: restore the model.

How do I load a TensorFlow in Python?

1. In the command prompt start a python session using the command >python.
2. Import the tensorflow package using :- > import tensorflow as tf.
3. Check for tensorflow version that has been installed. > tf.__version__ Above three steps has been summarized in the snapshot below:-

How do I save a Tensorflow model in python?

It is advised to use the save() method to save h5 models instead of save_weights() method for saving a model using tensorflow. However, h5 models can also be saved using save_weights() method.

How do I open a .PB file in Windows?

4 Easy Ways to Open {PB Files

1. Use Another Program. If you can’t view the {PB file by double-clicking it, try opening it in a different program.
2. Get a Clue From the File Type. One file extension can be used for multiple types of files.
3. Contact a Developer.
4. Get a Universal File Viewer.
5. Recommended Download.

What does TensorFlow use to save and restore model parameters on the disk?

The model restoring is done using the tf. saved_model. loader and restores the saved variables, signatures, and assets in the scope of a session.

How do you save tensor in TensorFlow?

To save and restore your variables, all you need to do is to call the tf. train. Saver() at the end of you graph. This will create 3 files ( data , index , meta ) with a suffix of the step you saved your model.

How do I add Tensorflow to PyCharm?

Your answer

1. For PyCharm firstly, go to file then settings.
2. Now click on the plus sign(+) which is shown top of right side of new pop-up window.
3. Then type TensorFlow and select the required version by going to a specific version option which is specified right side of the bottom.
4. Now click on the install package.

How do I import a Tensorflow in Python Jupyter notebook?

1. install tensorflow by running these commands in anoconda shell or in console: conda create -n tensorflow python=3.5 activate tensorflow conda install pandas matplotlib jupyter notebook scipy scikit-learn pip install tensorflow.
2. close the console and reopen it and type these commands: activate tensorflow jupyter notebook.

What is the PB format in TensorFlow?

The .pb format is the protocol buffer (protobuf) format, and in Tensorflow, this format is used to hold models. Protobufs are a general way to store data by Google that is much nicer to transport, as it compacts the data more efficiently and enforces a structure to the data.

What file formats can I save an entire model in TensorFlow?

An entire model can be saved in two different file formats ( SavedModel and HDF5 ). The TensorFlow SavedModel format is the default file format in TF2.x. However, models can be saved in HDF5 format. More details on saving entire models in the two file formats is described below.

Can I resume training from the optimizer-state in TensorFlow?

Since the optimizer-state is recovered, you can resume training from exactly where you left off. An entire model can be saved in two different file formats ( SavedModel and HDF5 ). The TensorFlow SavedModel format is the default file format in TF2.x. However, models can be saved in HDF5 format.

Why is my TensorFlow model getting different results for different weights?

You are freezing the graph properly that is why you are getting different results basically weights are not getting stored in your model. You can use the freeze_graph.py ( link) for getting a correctly stored graph. Here is the updated code for tensorflow 2. Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question.