Update documentation #411
Update documentation #411
Conversation
al-rigazzi
requested review from
amandarichardsonn,
ashao,
MattToast and
mellis13
Codecov Report
Additional details and impacted files@@ Coverage Diff @@
## develop #411 +/- ##
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doc/contributing.rst
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| bring your contribution into the codebases by testing it across a variety of | ||
| platforms and ensuring code quality. | ||
| bring your contribution into the codebases by testing it across a variety of | ||
| platforms and ensuring code quality. | ||
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| - You will be credited as a co-author when the contribution is merged |
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Period at the end of this to match other formatting
| client.run_script("normalizer", "normalize", inputs=["X_rand"], outputs=["X_norm"]) | ||
| x_norm = client.get_tensor("X_norm") | ||
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| Notice that the key ``"normalizer"`` represents the script containing the function (similar to |
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Do you mind adding more information here? I think it might be easier to understand if you provided more guidance during the 'Notice' sentence, possibly point out run_script() or specifically where the function and script are named, I might split the code up into parts as well -> describe set_function(), describe run_script()
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I added in-line comments to avoid breaking the code block. Let me know if it is more understandable now!
doc/ml_features.rst
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| for language-specific details. | ||
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| Using ML models on the DB | ||
| ========================= |
| client.run_script("normalizer", "normalize", inputs=["X_rand"], outputs=["X_norm"]) | ||
| x_norm = client.get_tensor("X_norm") | ||
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| Notice that the key ``"normalizer"`` represents the script containing the function (similar to |
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I added in-line comments to avoid breaking the code block. Let me know if it is more understandable now!
doc/ml_features.rst
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| TensorFlow and Keras models <smartsim_tf_api>`: ``freeze_model`` and | ||
| ``serialize_model``. | ||
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| The method ``freeze_model`` is thought to be used in conjunction |
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Let's skip the full source code, as the page will be already quite long. What do you think?
| client.run_script("shifter", "shift_y_to_x", inputs=["X_rand", "Y_rand"], outputs=["Y_scaled"]) | ||
| # Download output | ||
| y_scaled = client.get_tensor("Y_scaled") | ||
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I would add a mini end summary here, something like Notice how I use the function Client.set_script_from_file() to upload the script to the DB, then call the script from within the DB via Client.run_script(), the output tensors are stored in the DB so I use get_tensor to retrieve
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ermmm I see you actually have this in the code comments, maybe its actually fine
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I am able to understand it and follow by reading the comments btw!
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Added a small recap anyhow!
| @@ -46,6 +47,7 @@ | |||
| sr_data_structures | |||
| sr_dataset_conversions | |||
| sr_runtime | |||
| sr_advanced_topics | |||
This PR adds a section, named ML Features, to the SmartSim documentation. The section currently has subsections explaining how to upload PyTorch, TensorFlow, and ONNX models and functions to the DB.
The Online Analysis tutorial notebook was also enriched with TorchScript post-processing functions which show how the TorchScript mechanism works.
Other minor typos and documentation inconsistencies were fixed as part of this PR.