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cgraph (version 6.0.1)

Computational Graphs

Description

Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various operations including basic arithmetic, trigonometry operations, and linear algebra operations. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.

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Version

Install

install.packages('cgraph')

Version

6.0.1

License

Apache License 2.0

Maintainer

Last Published

February 9th, 2020

Functions in cgraph (6.0.1)

cg_dim

Dimensions of an Array
cg_cosh

Hyperbolic Cosine
cg_div

Divide
cg_function

Create function
cg_atanh

Inverse Hyperbolic Tangent
cg_log2

Logarithm Base 2
cg_log10

Logarithm Base 10
cg_atan

Inverse Tangent
cg_crossprod

Matrix Crossproduct
cg_exp

Exponential Function
cg_rowsums

Row Sums
cg_session_graph

Get Active Graph
cg_sin

Sine
cg_constant

Add Constant
cg_sinh

Hyperbolic Sine
cg_tan

Tangent
cg_graph

Computational Graph
cg_t

Matrix Transpose
cg_colmeans

Column Means
cg_colsums

Column Sums
cg_acos

Inverse Cosine
cg_mul

Multiply
cg_graph_backward

Backward Pass
cg_ln

Natural Logarithm
cg_nrow

Number of Rows of an Array
cg_operator

Add Operator
cg_neg

Negative
cg_ncol

Number of Columns of an Array
cg_linear

Linear Transformation
cg_cos

Cosine
cg_sub

Subtract
cg_subset1

Subset
cg_parameter

Add Parameter
cg_pos

Positive
cg_square

Square
cg_sqrt

Square Root
cg_pow

Power
cg_input

Add Input
cg_tcrossprod

Transpose Matrix Crossproduct
cg_tanh

Hyperbolic Tangent
cg_graph_forward

Forward Pass
cg_mean

Arithmetic Mean
cg_graph_get

Retrieve Node
cg_min

Minima
cg_length

Length of an Object
cg_prod

Product of Vector Elements
cg_rowmeans

Row Means
cg_sum

Sum of Vector Elements
cg_subset2

Subset
cg_max

Maxima
cg_pmax

Parallel Maxima
cg_pmin

Parallel Minima
cg_matmul

Matrix Multiplication
cg_session_set_graph

Change Active Graph
cg_sigmoid

Sigmoid
dots

Capture Ellipsis
approx_gradient

Approximate Gradient
bsum

Block Summation
cg_abs

Absolute Value
cg_acosh

Inverse Hyperbolic Cosine
cg_add

Add
cg_as_numeric

Coerce to a Numerical Vector
cg_as_double

Coerce to a Numerical Vector
cg_asin

Inverse Sine
cg_asinh

Inverse Hyperbolic Sine