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In OCaml, the library function Oo.copy performs shallow copying of an object. In Python, the library's copy module provides shallow copy and deep copy of objects through the copy() and deepcopy() functions, respectively. [13] Programmers may define special methods __copy__() and __deepcopy__() in an object to provide custom copying implementation.
In computer science, cloning refers to the making of an exact copy of an object, frequently under the paradigm of instance-based programming, or object-oriented programming (OOP). Shallow copies [ edit ]
Each element of a slice is a shallow copy. In Python, a distinction between expressions and statements is rigidly enforced, in contrast to languages such as Common Lisp, Scheme, or Ruby. This leads to duplicating some functionality. For example: List comprehensions vs. for-loops; Conditional expressions vs. if blocks
However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against ...
In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop.All generators are also iterators. [1] A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values.
This page was last edited on 31 May 2015, at 18:45 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply ...
This is the distribution in function space corresponding to the distribution () in parameter space, and the black dots are samples from this distribution. For infinitely wide neural networks, since the distribution over functions computed by the neural network is a Gaussian process, the joint distribution over network outputs is a multivariate ...
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.