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parameter.jl
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parameter.jl
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export Parameter
export make_parameter, share_parameter
type Parameter <: AbstractParameter
name :: AbstractString
blob :: Blob
gradient :: Blob
initializer :: Initializer
regularizer :: Regularizer
constraint :: Constraint
learning_rate :: AbstractFloat # relative learning rate
rc :: RefCounter
end
# construct a new parameter
Parameter(name,blob,gradient,initializer,regularizer,constraint,lr) =
Parameter(name, blob, gradient, initializer, regularizer, constraint, lr, RefCounter(1))
function make_parameter{N}(backend::Backend, name::AbstractString, data_type::Type, dims::NTuple{N,Int},
init::Initializer, regu::Regularizer, cons::Constraint, lr::AbstractFloat)
blob = make_blob(backend, data_type, dims)
grad = make_blob(backend, data_type, dims)
rc = RefCounter(1)
Parameter(name, blob, grad, init, regu, cons, lr, rc)
end
# make a shared parameter
function share_parameter(backend::Backend, param::Parameter)
blob = param.blob
grad = make_blob(backend, eltype(blob), size(blob))
init = NullInitializer()
regu = param.regularizer
cons = param.constraint
lr = param.learning_rate
rc = ref(param.rc)
Parameter(param.name, blob, grad, init, regu, cons, lr, rc)
end
function destroy(param::Parameter)
destroy(param.gradient)
if dec(param.rc) == 0
destroy(param.blob)
end
end