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Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all possible values of some integer type. For example, float might be an IEEE 754 single precision type, which cannot represent the integer 16777217 exactly, while a 32-bit integer type ...
However, hardware support for accelerated 16-bit floating point was later dropped by Nvidia before being reintroduced in the Tegra X1 mobile GPU in 2015. The F16C extension in 2012 allows x86 processors to convert half-precision floats to and from single-precision floats with a machine instruction.
Besides integers, floating-point numbers, and Booleans, other built-in types include: The void type and null pointer type nullptr_t in C++11 and C23; Characters and strings (see below) Tuple in Standard ML, Python, Scala, Swift, Elixir; List in Common Lisp, Python, Scheme, Haskell; Fixed-point number with a variety of precisions and a ...
The standard type hierarchy of Python 3. In computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. [1]
A decimal data type could be implemented as either a floating-point number or as a fixed-point number. In the fixed-point case, the denominator would be set to a fixed power of ten. In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied.
import theano from theano import tensor # Declare two symbolic floating-point scalars a = tensor. dscalar b = tensor. dscalar # Create a simple expression c = a + b # Convert the expression into a callable object that takes (a, b) # values as input and computes a value for c f = theano. function ([a, b], c) # Bind 1.5 to 'a', 2.5 to 'b', and evaluate 'c' assert 4.0 == f (1.5, 2.5)
The "decimal" data type of the C# and Python programming languages, and the decimal formats of the IEEE 754-2008 standard, are designed to avoid the problems of binary floating-point representations when applied to human-entered exact decimal values, and make the arithmetic always behave as expected when numbers are printed in decimal.
The IEEE Standard for Floating-Point Arithmetic (IEEE 754) is a technical standard for floating-point arithmetic originally established in 1985 by the Institute of Electrical and Electronics Engineers (IEEE). The standard addressed many problems found in the diverse floating-point implementations that made them difficult to use reliably and ...