Python utilities used by Deep Procedural Intelligence
Project description
DPU Utilities
This contains a set of utilities used across projects of the DPU team.
Python
Stored in the python
subdirectory, published as the dpu-utils
package.
Installation
pip install dpu-utils
Overview of Utilities:
Generic Utilities:
dpu_utils.utils.RichPath
a convenient way of using both paths and Azure paths in your code.dpu_utils.utils.*Iterator
iterator wrappers that can parallelize their iteration in other threads/processes.dpu_utils.utils.{load,save}_json[l]_gz
convenience methods for loading .json[l].gz from the filesystem.dpu_utils.utils.git_tag_run
that tags the current working directory git the state of the code.dpu_utils.utils.run_and_debug
when an exception happens, start a debug session. Usually a wrapper of__main__
.dpu_utils.utils.ChunkWriter
that helps writing chunks to the output.
TensorFlow Utilities:
dpu_utils.tfutils.GradRatioLoggingOptimizer
a wrapper around optimizers that logs the ratios of grad norms to parameter norms.dpu_utils.tfutils.unsorted_segment_logsumexp
dpu_utils.tfutils.unsorted_segment_log_softmax
dpu_utils.tfutils.TFVariableSaver
save TF variables in an object that can be pickled.
General Machine Learning Utilities:
dpu_utils.mlutils.CharTensorizer
for character-level tensorization.dpu_utils.mlutils.Vocabulary
a str to int vocabulary for machine learning models
TensorFlow Models:
dpu_utils.tfmodels.SparseGGNN
a sparse GGNN implementation.dpu_utils.tfmodels.AsyncGGNN
an asynchronous GGNN implementation.
Code-related Utilities
dpu_utils.codeutils.split_identifier_into_parts()
split identifiers into subtokens on CamelCase and snake_case.dpu_utils.codeutils.{Lattice, CSharpLattice}
represent lattices and some useful operations in Python.dpu_utils.codeutils.get_language_keywords()
that retrieves the keyword tokens for many programming languages.dpu_utils.codeutils.deduplication.DuplicateDetector
that detects duplicates in codebases.
Command-line tools
Approximate Duplicate Code Detection
You can use the deduplicationcli
command to detect duplicates in pre-processed source code, by invoking
deduplicationcli DATA_PATH OUT_JSON
where DATA_PATH
is a file containing tokenized .jsonl.gz
files and OUT_JSON
is the target output file.
For more options look at --help
.
An exact (but usually slower) version of this can be found here along with code to tokenize Java, C#, Python and JavaScript into the relevant formats.
Tests
Run the unit tests
python setup.py test
Generate code coverage reports
# pip install coverage
coverage run --source dpu_utils/ setup.py test && \
coverage html
The resulting HTML file will be in htmlcov/index.html
.
.NET
Stored in the dotnet
subdirectory.
Generic Utilities:
Microsoft.Research.DPU.Utils.RichPath
: a convenient way of using both paths and Azure paths in your code.
Code-related Utilities:
Microsoft.Research.DPU.CSharpSourceGraphExtraction
: infrastructure to extract Program Graphs from C# projects.
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
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