<p><strong>Answer to Question 1</strong></p>
<p>TensorFlow's <a href="https://www.tensorflow.org/api_docs/python/tf/keras/saving/save_model#:%7E:text=With%20save_format%3D%22tf%22%20%2C,are%20included%20in%20the%20SavedModel." rel="nofollow noreferrer">documentation</a> provides the following information on what is saved:</p>
<blockquote>
<p>The model config, weights, and optimizer are included in the SavedModel. Additionally, for every Keras layer attached to the model, the SavedModel stores:</p>
<ul>
<li>The config and metadata -- e.g. name, dtype, trainable status</li>
<li>Traced call and loss functions, which are stored as TensorFlow subgraphs.</li>
</ul>
</blockquote>
<p>You can use <a href="https://www.tensorflow.org/tensorboard/graphs#:%7E:text=TensorBoard%27s%20Graphs%20dashboard%20is%20a,how%20TensorFlow%20understands%20your%20program." rel="nofollow noreferrer">TensorBoard's Graphs dashboard</a> to visualize your model.</p>
<p>For a quick dive watch <a href="https://youtu.be/Uzkhn5ENJzQ?t=434" rel="nofollow noreferrer">Tensorboard with Tensorflow 2.0 under 10 mins</a>.</p>
<p><strong>Answer to Question 2</strong></p>
<p>See jdehesa's answer to a similar question regarding TF and H5 files: <a href="https://stackoverflow.com/questions/61006270/what-is-the-difference-between-pb-savedmodel-and-tf-savedmodel">What is the difference between .pb SavedModel and .tf</a></p>
<p><strong>Answer to Question 3</strong></p>
<p>Yes. Both formats, .pb and .tf, are used to save meaningful data and are used for reading in the models.</p>

CC BY-SA 4.0
2023-06-20T02:46:07.757Z
so based on your answer, is it true that most ML models are saved in a similar architecture that contains model config, weights, and optimizer? Or I think what I really want to ask is, how do I read information from ML model files of any format, regardless if it was trained with Tensorflow or Pytorch.
Ryan Wang
CC BY-SA 4.0
2023-06-19T04:11:29.553Z
2023-06-19T04:18:45.103Z
2023-06-19T04:18:45.103Z
Brian O'Donnell
<p>I'm building a feature for my application that requires <strong>reading the properties of a saved ML model file</strong> (after it's trained). However, as I am pretty new to this field, I don't really understand the foundational knowledge about developing AI, only knowing that parameters are trained and saved. I have some experience with the Tensorflow framework, and I know that a model can be saved in either a <code>Savedmodel</code> file or a <code>h5</code> file.</p>
<p>My questions are:</p>
<ol>
<li>What is actually being saved in those files typically? And what does it look like?</li>
<li>Is it a big difference when you save your model differently? for example <code>h5</code> vs <code>savedmodel</code> or tensorflow vs pytorch.</li>
<li>Is it possible for me to read meaningful information from any saved files regardless of the format? <em>So it doesn't matter if someone else used Pytorch, Tensorflow, or C to do ML</em></li>
</ol>

CC BY-SA 4.0
2023-06-20T11:49:40.087Z
Your questions seem to be off-topic here. They are mostly programming questions and specific to frameworks. We focus on the theoretical/non-programming aspects of AI.
nbro
<machine-learning><tensorflow><pytorch><models><weights>
What is actually being saved in the file when you save a model? For example a Tensorflow SavedModel file
Ryan Wang
# What is actually being saved in the file when you save a model? For example a Tensorflow SavedModel file

(Asked by: username_0 on 2023-06-19)

I'm building a feature for my application that requires **reading the properties of a saved ML model file** (after it's trained). However, as I am pretty new to this field, I don't really understand the foundational knowledge about developing AI, only knowing that parameters are trained and saved. I have some experience with the Tensorflow framework, and I know that a model can be saved in either a `Savedmodel` file or a `h5` file.

My questions are:

1. What is actually being saved in those files typically? And what does it look like?
2. Is it a big difference when you save your model differently? for example `h5` vs `savedmodel` or tensorflow vs pytorch.
3. Is it possible for me to read meaningful information from any saved files regardless of the format? *So it doesn't matter if someone else used Pytorch, Tensorflow, or C to do ML*

**Tags:** machine-learning, tensorflow, pytorch, models, weights

> **Comments:**
> **username_1**: Your questions seem to be off-topic here. They are mostly programming questions and specific to frameworks. We focus on the theoretical/non-programming aspects of AI.  

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## 1 answers

### Answer by username_2 on 2023-06-19. Score: 3

**Answer to Question 1**

TensorFlow's [documentation](https://www.tensorflow.org/api_docs/python/tf/keras/saving/save_model#:%7E:text=With%20save_format%3D%22tf%22%20%2C,are%20included%20in%20the%20SavedModel.) provides the following information on what is saved:

> The model config, weights, and optimizer are included in the SavedModel. Additionally, for every Keras layer attached to the model, the SavedModel stores:
>
> * The config and metadata -- e.g. name, dtype, trainable status
> * Traced call and loss functions, which are stored as TensorFlow subgraphs.

You can use [TensorBoard's Graphs dashboard](https://www.tensorflow.org/tensorboard/graphs#:%7E:text=TensorBoard%27s%20Graphs%20dashboard%20is%20a,how%20TensorFlow%20understands%20your%20program.) to visualize your model.

For a quick dive watch [Tensorboard with Tensorflow 2.0 under 10 mins](https://youtu.be/Uzkhn5ENJzQ?t=434).

**Answer to Question 2**

See jdehesa's answer to a similar question regarding TF and H5 files: [What is the difference between .pb SavedModel and .tf](https://stackoverflow.com/questions/61006270/what-is-the-difference-between-pb-savedmodel-and-tf-savedmodel)

**Answer to Question 3**

Yes. Both formats, .pb and .tf, are used to save meaningful data and are used for reading in the models.

> **Comments:**
> **username_0**: so based on your answer, is it true that most ML models are saved in a similar architecture that contains model config, weights, and optimizer? Or I think what I really want to ask is, how do I read information from ML model files of any format, regardless if it was trained with Tensorflow or Pytorch.  

---

