numpy.square — NumPy v1.23 Manual
A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized. For other keyword-only arguments, see the ufunc docs. Element-wise x*x, of the same shape and dtype as x. This is a scalar if x is a scalar. See also Examples Previous numpy.cbrt Next numpy.absolute © Copyright 2008-2022, NumPy Developers. Created using Sphinx 4.5.0.
numpy.square(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature]) = <ufunc 'square'># Return the element-wise square of the input. Parameters: xarray_like Input data. outndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. wherearray_like, optional This condition is…
saved by
related reading
- GitHub - srush/Tensor-Puzzles: Solve puzzles. Improve your pytorch.github.com
- Desmos | Scientific Calculatordesmos.com
- Plus 2: Luyện đọc điền và đọc hiểu chuyên sâu (2024)ngoaingu24h.vn
- How to think in JAX — JAX documentationdocs.jax.dev
- Chữa Đề số 01ngoaingu24h.vn
- HackerRank - Online Coding Tests and Technical Interviewshackerrank.com
- torch.stackdocs.pytorch.org
- torch.where — PyTorch 2.12 documentationdocs.pytorch.org
- GitHub - jax-ml/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and moregithub.com
- Chapter 0: Fundamentals - ARENAlearn.arena.education
- GitHub - Experience-Monks/math-as-code: a cheat-sheet for mathematical notation in code formgithub.com
- Arithmetic Game – Online Speed Drillarithmetic.zetamac.com