| /dports/databases/arrow/apache-arrow-6.0.1/docs/source/java/ |
| H A D | vector_schema_root.rst | 28 (see `Numba <https://github.com/apache/arrow/tree/master/java/flight/src/main/java/org/apache/arrow…
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| /dports/security/vault/vault-1.8.2/vendor/github.com/apache/arrow/docs/source/java/ |
| H A D | vector_schema_root.rst | 28 (see `Numba <https://github.com/apache/arrow/tree/master/java/flight/src/main/java/org/apache/arrow…
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| /dports/www/grafana8/grafana-8.3.6/vendor/github.com/apache/arrow/python/pyarrow/ |
| H A D | _cuda.pyx | 68 Create a Context instance from a Numba CUDA context.
73 A Numba CUDA context instance.
74 If None, the current Numba context is used.
89 Convert Context to a Numba CUDA context.
94 Numba CUDA context instance.
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| /dports/databases/arrow/apache-arrow-6.0.1/python/pyarrow/ |
| H A D | _cuda.pyx | 68 Create a Context instance from a Numba CUDA context.
73 A Numba CUDA context instance.
74 If None, the current Numba context is used.
89 Convert Context to a Numba CUDA context.
94 Numba CUDA context instance.
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| /dports/security/vault/vault-1.8.2/vendor/github.com/apache/arrow/python/pyarrow/ |
| H A D | _cuda.pyx | 68 Create a Context instance from a Numba CUDA context.
73 A Numba CUDA context instance.
74 If None, the current Numba context is used.
89 Convert Context to a Numba CUDA context.
94 Numba CUDA context instance.
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| /dports/finance/py-quantecon/quantecon-0.5.2/ |
| H A D | CHANGELOG.md | 16 1. ENH: [Add Numba-jitted linprog solver](https://github.com/QuantEcon/QuantEcon.py/pull/532) ([[oy…
72 - \[Tests\] Build fails with Numba 0.49.0 [\#530](https://github.com/QuantEcon/QuantEcon.py/issues/…
80 - FIX: Updates for Numba 0.49.0 [\#531](https://github.com/QuantEcon/QuantEcon.py/pull/531) ([oyama…
144 - Error in `sample\_without\_replacement` with Numba 0.43.0 [\#478](https://github.com/QuantEcon/Qu…
300 - Add Numba jit version of scipy.special.comb [\#377](https://github.com/QuantEcon/QuantEcon.py/pul…
560 - Importing without Numba [\#214](https://github.com/QuantEcon/QuantEcon.py/issues/214)
581 - \[Dependancy\] Propose introduction of dependancy on Numba [\#173](https://github.com/QuantEcon/Q…
633 - Update MarkovChain with ``replicate `` method and Future Numba Improvements [\#146](https://githu…
646 - Numba version of mc\_sample\_path [\#137](https://github.com/QuantEcon/QuantEcon.py/issues/137)
647 - Numba warning --- implement a common warning [\#133](https://github.com/QuantEcon/QuantEcon.py/is…
[all …]
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| /dports/science/py-pygmo2/pygmo2-2.18.0/doc/tutorials/ |
| H A D | coding_udp_simple.rst | 271 .. note:: For more information on using Numba to speed up your python code see the `Numba documenta…
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| /dports/devel/py-numba/numba-0.51.2/docs/source/cuda/ |
| H A D | simulator.rst | 8 Numba includes a CUDA Simulator that implements most of the semantics in CUDA
|
| /dports/science/py-scipy/scipy-1.7.1/doc/source/dev/ |
| H A D | roadmap.rst | 40 making it easier for users to use Numba's ``@njit`` in their code that relies
|
| /dports/math/py-iminuit/iminuit-2.8.4/ |
| H A D | PKG-INFO | 57 - Support for Numba accelerated functions (optional)
|
| /dports/math/py-iminuit/iminuit-2.8.4/src/iminuit.egg-info/ |
| H A D | PKG-INFO | 57 - Support for Numba accelerated functions (optional)
|
| /dports/math/py-arviz/arviz-0.11.4/arviz/stats/ |
| H A D | stats.py | 23 from ..utils import Numba, _numba_var, _var_names, get_coords
1004 _numba_flag = Numba.numba_flag
1245 _numba_flag = Numba.numba_flag
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| /dports/devel/py-dask/dask-2021.11.2/docs/source/ |
| H A D | array-best-practices.rst | 16 to consider a project like `Numba <https://numba.pydata.org>`_
|
| H A D | graphs.rst | 150 Cython, Numba, ctypes or others.
|
| H A D | phases-of-computation.rst | 115 Cython, Numba, or any other solution that is commonly used to accelerate Python
|
| H A D | best-practices.rst | 34 - **Compiled code**: Compiling your Python code with Numba or Cython might
245 If you're doing mostly numeric work with Numpy, Pandas, Scikit-Learn, Numba,
|
| H A D | dataframe-best-practices.rst | 246 implementation that uses the `Numba <https://numba.pydata.org/>`_
|
| /dports/lang/cython-devel/cython-2b1e743/ |
| H A D | README.rst | 73 * `Numba <http://numba.pydata.org/>`_, a Python extension that features a
|
| /dports/devel/py-numba/numba-0.51.2/docs/source/user/ |
| H A D | cfunc.rst | 206 The explicit ``@cfunc`` signature can use any :ref:`Numba types <numba-types>`,
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| /dports/math/py-pandas/pandas-1.2.5/doc/source/user_guide/ |
| H A D | groupby.rst | 1084 Numba Accelerated Routines
1089 If `Numba <https://numba.pydata.org/>`__ is installed as an optional dependency, the ``transform`` …
1107 In terms of performance, **the first time a function is run using the Numba engine will be slow**
1108 … as Numba will have some function compilation overhead. However, the compiled functions are cached,
1109 and subsequent calls will be fast. In general, the Numba engine is performant with
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| /dports/math/py-numpy/numpy-1.20.3/doc/source/reference/random/ |
| H A D | index.rst | 244 Examples of using Numba, Cython, CFFI <extending>
|
| /dports/devel/py-xarray/xarray-0.20.1/doc/ |
| H A D | ecosystem.rst | 43 - `xarray-spatial <https://makepath.github.io/xarray-spatial>`_: Numba-accelerated raster-based spa…
|
| /dports/devel/py-numba/numba-0.51.2/docs/source/proposals/ |
| H A D | jit-classes.rst | 12 Numba does not yet support user-defined classes.
|
| /dports/net/py-mpi4py/mpi4py-3.1.3/docs/source/usrman/ |
| H A D | overview.rst | 223 CuPy, Numba, PyTorch, and PyArrow. In order to increase library
226 example, a CuPy array can be passed to a Numba CUDA-jit kernel.
|
| /dports/math/py-numpy/numpy-1.20.3/doc/neps/ |
| H A D | nep-0044-restructuring-numpy-docs.rst | 106 - Performance (memory layout, profiling, use with Numba, Cython, or Pythran)
|