https://github.com/cambridge-iccs/process_model
The process_model tool reads a TensorFlow SavedModel and outputs Fortran code to interface it to the fortran-tf-lib
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
2 of 5 committers (40.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (7.3%) to scientific vocabulary
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Repository
The process_model tool reads a TensorFlow SavedModel and outputs Fortran code to interface it to the fortran-tf-lib
Basic Info
Statistics
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 1
- Releases: 0
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Metadata Files
README.md
process_model
The process_model tool reads a TensorFlow SavedModel and outputs Fortran code to interface it to the fortran-tf-lib
Installing
In a suitable Python environment do:
pip install git+https://github.com/Cambridge-ICCS/process_model.git
Note that as of 20/01/23 there is no tensorflow package in Pypi for Python >= 3.11.
Running the tool
The pip install will place a process_model command in the PATH. To use it, run it against one
or more TensorFlow SavedModel models.
process_model model_1 model_2 ...
The tool will output Fortran code to standard output, or to the file
specified with the -o option.
Using the resulting Fortran
The output is a module, named ml_module by default. It has procedures called
ml_module_init, ml_module_calc, ml_module_finish.
It also may have some *_associate_tensor routines tailored for the inputs
of the model. So if the model expects a Tensor of type TF_FLOAT and of shape
[-1, 40] then there will be a r32_2_associate_tensor routine to generate
appropriately shaped and typed tensors from Fortran arrays.
The ml_module_init routine should be called once, before using calc. It loads
the models into module variables.
Worked example
API reference
Owner
- Name: Institute of Computing for Climate Science
- Login: Cambridge-ICCS
- Kind: organization
- Website: https://cambridge-iccs.github.io/
- Twitter: Cambridge_ICCS
- Repositories: 8
- Profile: https://github.com/Cambridge-ICCS
Institute of Computing for Climate Science at the University of Cambridge
GitHub Events
Total
Last Year
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Simon Clifford | s****6@c****k | 9 |
| Simon Clifford | S****d | 4 |
| Valentin Churavy | v****y | 4 |
| Simon Clifford | s****d@i****k | 1 |
| Jia | j****h@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 2 years ago
All Time
- Total issues: 3
- Total pull requests: 4
- Average time to close issues: 10 days
- Average time to close pull requests: about 6 hours
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 0.33
- Average comments per pull request: 0.0
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 2
- Average time to close issues: 7 minutes
- Average time to close pull requests: about 13 hours
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- SimonClifford (2)
- Beliavsky (1)
Pull Request Authors
- SimonClifford (4)
Top Labels
Issue Labels
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Dependencies
- actions/cache v3 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- Click *
- jinja2 *
- tensorflow *