目录 收起 安装-Install(on Linux) 问题-problem1 解决-solution1 安装-Install(on Linux) 这是官网对于安装的说明: GitHub - google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and moregithub.com/google/jax?tab=readme-ov-file#installatio...
A stand-alone implementation of several NumPy dtype extensions used in machine learning. - jax-ml/ml_dtypes
I would like to save and load an f8m5e2 array. I initially tried using the standard numpy.save() and numpy.load() functions, but loading fails. .local/lib/python3.10/site-packages/numpy/lib/format.py", line 325, in descr_to_dtype return ...
Projects Security Insights Additional navigation options Files main .github .vscode ml_dtypes _src common.h custom_float.h dtypes.cc intn_numpy.h numpy.cc numpy.h ufuncs.h include tests __init__.py _finfo.py _iinfo.py py.typed third_party ...
DESCRIPTION="A stand-alone implementation of several NumPy dtype extensions" HOMEPAGE="https://github.com/jax-ml/ml_dtypes" SRC_URI=" https://github.com/jax-ml/${PN}/archive/refs/tags/v${PV}.tar.gz -> ${P}.gh.tar.gz https://github.com/jax-ml/${PNGH}/archive/refs/tags/v${PV...
A stand-alone implementation of several NumPy dtype extensions used in machine learning. - ml_dtypes/pyproject.toml at main · jax-ml/ml_dtypes
np.ndarray of bfloat16 using ml_dtypes is being interpreted as complex64 by mlx. To Reproduce >>> from ml_dtypes import bfloat16 >>> import numpy as np >>> x = np.array(1., dtype=bfloat16) >>> import mlx.core as mx >>> mx.array(x) array(1+0j, dtype=complex64) >>> ...
#include "ml_dtypes/_src/numpy.h" //NOLINT // clang-format on #include <array> // NOLINT @@ -31,11 +31,11 @@ limitations under the License. #include <Python.h> #include "Eigen/Core" #include "_src/custom_float.h" #include "_src/intn_numpy.h" #include "include/float8.h" ...
300 + if (!RegisterFloatDtype<float8_e3m4>(numpy.get())) { 301 + return false; 302 + } 286 303 if (!RegisterFloatDtype<float8_e4m3>(numpy.get())) { 287 304 return false; 288 305 } @@ -342,6 +359,13 @@ bool Initialize() { 342 359 success &= RegisterTwoWayCust...
jakevdp:ci-oldest-numpy June 26, 2024 18:58 30m 58s CI: add test against oldest supported numpy Test #386: Pull request #157 synchronize by jakevdp jakevdp:ci-oldest-numpy June 26, 2024 18:58 2m 3s Push on main CodeQL #182: by github-advanced-security bot June 26, 2024...