Disable Safe Mode Shortcut in the data directory Safe Mode key binding can be disabled by creating a file named.Added reveal_menu setting for disabling revealing the menu when alt is pressed on Linux and Windows.Preserve Case now works with unicode characters.Middle clicking in the Open Files section of then sidebar will close the clicked on file.Theme: Fixed adaptive theme not respecting themed_title_bar setting with light color schemes.

Added syntax_detection_size_limit setting for controlling when syntax detection is skipped.

Syntax and indentation detection is now done when editing stdin.

subl can now be used to edit stdin, eg: echo test | subl | cat.

Various syntax highlighting improvements.

Improved performance when editing large files.

Tensor learning, algebra and backends to seamlessly use NumPy, MXNet, PyTorch, TensorFlow or CuPy. Python backend system that decouples API from implementation unumpy provides a NumPy API. Multi-dimensional arrays with broadcasting and lazy computing for numerical analysis.ĭevelop libraries for array computing, recreating NumPy's foundational concepts. NumPy-compatible sparse array library that integrates with Dask and SciPy's sparse linear algebra.ĭeep learning framework that accelerates the path from research prototyping to production deployment.Īn end-to-end platform for machine learning to easily build and deploy ML powered applications.ĭeep learning framework suited for flexible research prototyping and production.Ī cross-language development platform for columnar in-memory data and analytics. Labeled, indexed multi-dimensional arrays for advanced analytics and visualization NumPy-compatible array library for GPU-accelerated computing with Python.Ĭomposable transformations of NumPy programs: differentiate, vectorize, just-in-time compilation to GPU/TPU. NumPy's API is the starting point when libraries are written to exploit innovative hardware, create specialized array types, or add capabilities beyond what NumPy provides.ĭistributed arrays and advanced parallelism for analytics, enabling performance at scale. With this power comes simplicity: a solution in NumPy is often clear and elegant.

NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. Nearly every scientist working in Python draws on the power of NumPy.

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