Python Inference Script(PyIS)
Python Inference Script is a Python package that enables developers to author machine learning workflows in Python and deploy without Python.
Various tools could be available for fast experimentation, for example sklearn, CNTK, Tensorflow, PyTorch and etc. However, when it comes to deployement, problems will emerge:
- Is it optimized, fast or memory efficient?
- Is the runtime or model compact enough for edge devices?
- Is it easy to learn or cross-platform?
To solve those puzzles, the Python Inference Script(PyIS) is introduced.
Build and install from source
from pip source (Coming Soon)
python -m pip install pyis-python --upgrade
# Python backend from pyis.python import ops from pyis.python.model_context import save, load # create trie op trie = ops.CedarTrie() trie.insert('what time is it in Seattle?') trie.insert('what is the time in US?') # run trie match query = 'what is the time in US?' is_matched = trie.contains(query) # serialize save(trie, 'tmp/trie.pkl') # load and run trie = load('tmp/trie.pkl') is_matched = trie.contains(query)
# LibTorch backend import torch from pyis.torch import ops from pyis.torch.model_context import save, load # define torch model class TrieMatcher(torch.nn.Module): def __init__(self): super().__init__() self.trie = ops.CedarTrie() self.trie.insert('what time is it in Seattle?') self.trie.insert('what is the time in US?') def forward(self, query: str) -> bool: return self.trie.contains(query) # create torch model model = torch.jit.script(TrieMatcher()) # run trie match query = 'what is the time in US?' is_matched = model.forward(query) # serialize save(model, 'tmp/trie.pt') # load and run model = load('tmp/trie.pt') is_matched = model.forward(query)
Build the Docs
Run the following commands and open
docs/_build/html/index.html in browser.
pip install sphinx myst-parser sphinx-rtd-theme sphinxemoji cd docs/ make html # for linux .\make.bat html # for windows
Please refer to CONTRIBUTING.md for the agreement and the instructions if you want to participate in this project.
The software may collect information about you and your use of the software and send it to Microsoft. Microsoft may use this information to provide services and improve our products and services. You may turn off the telemetry as described in the repository. There are also some features in the software that may enable you and Microsoft to collect data from users of your applications. If you use these features, you must comply with applicable law, including providing appropriate notices to users of your applications together with a copy of Microsoft’s privacy statement. Our privacy statement is located at https://go.microsoft.com/fwlink/?LinkID=824704. You can learn more about data collection and use in the help documentation and our privacy statement. Your use of the software operates as your consent to these practices.
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Code of Conduct
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT license.