Skip to main content

Python utilities used by Deep Procedural Intelligence

Project description

DPU Utilities

Build Status

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dpu_utils-0.1.35.tar.gz (29.9 kB view details)

Uploaded Source

Built Distribution

dpu_utils-0.1.35-py2.py3-none-any.whl (42.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file dpu_utils-0.1.35.tar.gz.

File metadata

  • Download URL: dpu_utils-0.1.35.tar.gz
  • Upload date:
  • Size: 29.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.8

File hashes

Hashes for dpu_utils-0.1.35.tar.gz
Algorithm Hash digest
SHA256 e778c5141957f24daf87cba142ece5d88b57d7e0ecc581bad0d84cdc0b84f8c6
MD5 af71081f8e7ae256125035b1305dbd2a
BLAKE2b-256 47cb1e3334b19d1752184bf770757fa1f7a5ec7a7b37c6dc64686819be4afccf

See more details on using hashes here.

File details

Details for the file dpu_utils-0.1.35-py2.py3-none-any.whl.

File metadata

  • Download URL: dpu_utils-0.1.35-py2.py3-none-any.whl
  • Upload date:
  • Size: 42.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.8

File hashes

Hashes for dpu_utils-0.1.35-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 0e62f158ece0a934176a48ff97e01305d32875d95140df4d5ac5cc31819a7438
MD5 33fb1e83d6101b2ac6b7d7d1a999c174
BLAKE2b-256 2821e8caa99bdbd9fb116f60e10b394b89cd191e22908b8570814e4df5903357

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page