module = CriterionTable(criterion)

Creates a module that wraps a Criterion module so that it can accept a Table of inputs. Typically the table would contain two elements: the input and output x and y that the Criterion compares.

Example: 

mlp = nn.CriterionTable(nn.MSECriterion())
require "lab"
x=lab.randn(5)
y=lab.randn(5)
print(mlp:forward{x,x})
print(mlp:forward{x,y})
gives the output: 
0
1.9028918413199

Here is a more complex example of embedding the criterion into a network: 

require "lab"

function table.print(t)
 for i,k in pairs(t) do print(i,k); end
end
 
mlp=nn.Sequential();                          -- Create an mlp that takes input
  main_mlp=nn.Sequential();		      -- and output using ParallelTable      
  main_mlp:add(nn.Linear(5,4)) 
  main_mlp:add(nn.Linear(4,3))
 cmlp=nn.ParallelTable(); 
 cmlp:add(main_mlp)
 cmlp:add(nn.Identity())           
mlp:add(cmlp)
mlp:add(nn.CriterionTable(nn.MSECriterion())) -- Apply the Criterion

for i=1,20 do                                 -- Train for a few iterations
 x=lab.ones(5);
 y=torch.Tensor(3); y:copy(x:narrow(1,1,3))
 err=mlp:forward{x,y}                         -- Pass in both input and output
 print(err)

 mlp:zeroGradParameters();
 mlp:backward({x, y} );   
 mlp:updateParameters(0.05); 
end