Search Results for "numpy python 3.4" - Page 2
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Showing 55 open source projects for "numpy python 3.4"
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1
Jittor
Jittor is a high-performance deep learning framework
...Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. ... -
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Flax
Flax is a neural network library for JAX
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging... -
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Faiss
Library for efficient similarity search and clustering dense vectors
...It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. ... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an... -
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5
Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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TensorNetwork
A library for easy and efficient manipulation of tensor networks
TensorNetwork is a high-level library for building and contracting tensor networks—graphical factorizations of large tensors that underpin many algorithms in physics and machine learning. It abstracts networks as nodes and edges, then compiles efficient contraction orders across multiple numeric backends so users can focus on model structure rather than index bookkeeping. Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage... -
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libpython-clj
Python bindings for Clojure
libpython-clj is a deep interop library enabling you to load and use Python modules from within Clojure as if they were native namespaces—and even extend Python objects from Clojure. It bridges to the Python C API, preserving REPL‑based workflows. Bridge between JVM objects and Python objects easily; use Python in your Java and use some Java in your Python. Python objects are linked to the JVM GC such that when they are no longer reachable from the JVM, their references are released.... -
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WALKOFF
A flexible, easy to use, automation framework
...Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and workflows. Deploy on Windows or Linux. Python 2.7 and 3.4+. Scale to your needs. Plug-and-play integration of almost anything with easy-to-develop apps. Send workflow data to custom visual interfaces to act with confidence. Harness the power of automation on your terms. An active community is essential for our success. Help us to develop and promote a common integration format that would enable the seamless deployment of WALKOFF apps across participating platforms. -
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pipupgrade
Like yarn outdated/upgrade, but for pip
pipupgrade is a command-line utility designed to streamline the management of Python package dependencies. It automates the process of identifying and upgrading outdated packages across various Python environments, including system-wide installations, virtual environments, and project-specific setups. By analyzing semantic versioning, pipupgrade categorizes updates into major, minor, and patch changes, allowing developers to make informed decisions about which packages to upgrade.... -
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rest-dev-vnc-docker
Restful / SOAP API Development with common tools in VNC/noVNC Docker
The idea is to use Docker with VNC/noVNC to aggregate all the needed and related Developments tools/IDEs within a single Docker as an agile way to stand up specific collections of tools quick within a Container quick computing needs. REST Development (this GIT) to cover end-to-end needs from JSON/XML, REST connection, Swagger, MongoDB, Test, etc. The use-cases of this kind of VNC/noVNC docker container is just limited by your imaginations and your device or network limitations. Virtually... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. -
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Aglyph
Aglyph is a Dependency Injection framework for Python.
Aglyph is a Dependency Injection framework for Python, supporting type 2 (setter) and type 3 (constructor) injection. Aglyph runs on CPython (http://www.python.org/) 2.7 and 3.4+, and on recent versions of the PyPy (http://pypy.org/>),Jython (http://www.jython.org/), IronPython (http://ironpython.net/), and Stackless Python (http://www.stackless.com/) variants. Aglyph can assemble "prototype" components (a new instance is created every time), "singleton" components (the same instance is returned every time), "borg" components (a new instance is created every time, but all instances of the same class share the same internal state), and "weakref" components (the same instance is returned as long as there is at least one "live" reference to the instance in the running application). ... -
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Tangent
Source-to-source debuggable derivatives in pure Python
...Tangent works on a large and growing subset of Python, provides extra autodiff features other Python ML libraries don't have, has reasonable performance, and is compatible with TensorFlow and NumPy. -
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform... -
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REST framework JWT Auth
JSON Web Token Authentication support for Django REST Framework
JSON Web Token Authentication support for Django REST Framework. This package provides JSON Web Token Authentication support for Django REST framework. Unlike some more typical uses of JWTs, this module only generates authentication tokens that will verify the user who is requesting one of your DRF protected API resources. The actual request parameters themselves are not included in the JWT claims which means they are not signed and may be tampered with. You should only expose your API... -
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coala
Coala provides a command-line interface for linting and fixing code
Coala provides a unified command-line interface for linting and fixing all your code, regardless of the programming languages you use. You can use Coala from within your favorite editor, integrate it with your CI, get the results as JSON, or customize it to your needs with its flexible configuration syntax. -
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Icon Font to PNG
Python script (and library) for exporting icons from icon fonts
Python script (and library) for easy and simple export of icons from web icon fonts (e.g. Font Awesome, Octicons) as PNG images. The best part is the provided shell script, but you can also use it’s functionality directly in your (probably awesome) Python project. There’s also font-awesome-to-png script for backward compatibility with the first iteration of the concept. You can use IconFont (and IconFontDownloader for that matter) directly inside your Python project. There's no proper... -
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Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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mds-utils
General purpose utilities for C++ and Python developers
...Amongst them, some type traits for detecting different uBLAS matrix types. 3. some useful classes that allow to treat the old C FILE pointer as a C++ stream. 4. C++ wrappers of the main Python objects, independent of those in Boost Python. Wrappers are provided also for NumPy arrays. 5. C++ classes that help on treating Python file objects as C++ streams. 6. a review and refactor of the indexing support in Python extensions. Now access in write mode is supported too. More details on the Doxygen documentation. ... -
20
PyCNN
Image Processing with Cellular Neural Networks in Python
Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high... -
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ASN.1 types and codecs (BER, CER, DER) implementation in Python programming language. A collection of various ASN.1-based protocols data structures is supplied in a dedicated Python package. Project moved to GitHub: https://github.com/etingof/pyasn1
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pure python polyfit
python2/3: compute polyfit (1D, 2D, N-D) without thirdparty libraries
python2/3: compute polyfit (1D, 2D, N-D) without any thirdparty library like numpy, scipy etc. also can be used for least squares solution computation and for A=QR matrix decomposition. Tested with python 2.7 and 3.4 Consider donating to this project: https://sourceforge.net/p/purepythonpolyfit/donation For a Sample use, refer to the WIKI -
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Based on PyQwt (plotting widgets for PyQt4 graphical user interfaces) and on the scientific modules NumPy and SciPy, guiqwt is a Python library providing efficient 2D data-plotting features (curve/image visualization and related tools) for interactiv
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Django Autocomplete Light
A fresh approach to autocomplete implementations
A fresh approach to autocomplete implementations, specially for Django. Python 2.7, 3.4, Django 2.0+ support (Django 1.11 (LTS), is supported until django-autocomplete-light-3.2.10), Django (multiple) choice support, Django (multiple) model choice support, Django generic foreign key support (through django-querysetsequence), Django generic many to many relation support (through django-generic-m2m and django-gm2m). -
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Boto3
AWS SDK for Python
...This allows us to provide very fast updates with strong consistency across all supported services. Boto3 was written from the ground up to provide native support in Python versions 2.7+ and 3.4+.
