What are Static and Dynamic networks in Dynet explain

This recipe explains what are Static and Dynamic networks in Dynet explain

Recipe Objective - What are Static and Dynamic networks in Dynet explain?

Static Network:-

Static Network, in which a network is constructed and afterward being taken care of with various sources of input and outputs.

Dynamic Network:-

Dynamic Network, in which another network is worked for each preparation model (offering boundaries to the network of other network models). This methodology is the thing that makes DyNet interesting, and where a large portion of its powers comes from.

Dynamic Network is nery similar to the static network. But in this we create a new network for each training.

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Life-Cycle:-

Step: 1

Create a "ParameterCollection".

Step: 2

Create "Expression" representing a network.

Step: 3

Optimization of model.

Example:-

import dynet as dy

# creating a parameter collection and add the parameters.
pc = dy.ParameterCollection()
par1 = m.add_parameters((8,2))
par2 = m.add_parameters((2,8))
par3 = m.add_parameters((8))

dy.renew_cg()

#b[1:-1].value()
par3.value()

x = dy.vecInput(2) # an input vector of size 2. Also an expression.
output = dy.logistic(par2*(dy.tanh((par1*x)+par3)))

# query the network
x.set([0,0])
output.value()

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