What are variables and parameters in chainer explain

This recipe explains what are variables and parameters in chainer explain

Recipe Objective - What are variables and parameters in chainer explain?

Variable is an array with a structure to keep track of computation.

Every variable holds a data array of type either numpy.ndarray or cupy.ndarray.

A variable object holds a data array and a VariableNode object of a computational graph. If the variable is constructed by the user, the node is root and does not hold any parent. If the variable is constructed by a FunctionNode object (i.e., by calling functions under chainer.functions or user-defined functions), or by using operators, the node holds a reference to its parent called creator_node. This reference is used in backpropagation to backtrack the graph.

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This are some of the operators which are defined for variable(s).

Addition: a + b

Indexing: b[slicer]

Subtraction: a - b

Multiplication: a * b

Division: a / b

Parameter is a subclass of Variable. It almost behaves as same as a usual variable except that a parameter can be registered to a Link object just by assigning it to an attribute of the link within an init_scope() context.

Parameter also supports an initialization by an initializer. It can have two initializers: one for the data array, and the other for the gradient array. The initializer only specifies the way of filling the elements of these arrays, and the shape information is specified at the initialization point.

When a link that the parameter has been registered to is passed to an GradientMethod, an update rule is set to the parameter. This update rule specifies how to update the data array of the parameter using its gradient array.

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