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comparison src/LazyTensors/lazy_tensor_operations.jl @ 412:d94891b8dfca feature/tensor_composition

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Start implementing TensorComposition
author Jonatan Werpers <jonatan@werpers.com>
date Thu, 15 Oct 2020 22:05:22 +0200
parents 1936e38fe51e
children 814865d40f48
comparison
equal deleted inserted replaced
410:26e186b565b3 412:d94891b8dfca
72 domain_size(tmBinOp::LazyTensorMappingBinaryOperation{Op,T,R,D}) where {Op,T,R,D} = domain_size(tmBinOp.tm1) 72 domain_size(tmBinOp::LazyTensorMappingBinaryOperation{Op,T,R,D}) where {Op,T,R,D} = domain_size(tmBinOp.tm1)
73 73
74 Base.:+(tm1::TensorMapping{T,R,D}, tm2::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:+,T,R,D}(tm1,tm2) 74 Base.:+(tm1::TensorMapping{T,R,D}, tm2::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:+,T,R,D}(tm1,tm2)
75 Base.:-(tm1::TensorMapping{T,R,D}, tm2::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:-,T,R,D}(tm1,tm2) 75 Base.:-(tm1::TensorMapping{T,R,D}, tm2::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:-,T,R,D}(tm1,tm2)
76 76
77 """
78 TensorMappingComposition{T,R,K,D}
77 79
78 # TODO: Write tests and documentation for LazyTensorMappingComposition 80 Lazily compose two TensorMappings, so that they can be handled as a single TensorMapping.
79 # struct LazyTensorMappingComposition{T,R,K,D} <: TensorMapping{T,R,D} 81 """
80 # t1::TensorMapping{T,R,K} 82 struct TensorMappingComposition{T,R,K,D, TM1<:TensorMapping{T,R,K}, TM2<:TensorMapping{T,K,D}} <: TensorMapping{T,R,D}
81 # t2::TensorMapping{T,K,D} 83 t1::TM1
82 # end 84 t2::TM2
83 85
84 # Base.:∘(s::TensorMapping{T,R,K}, t::TensorMapping{T,K,D}) where {T,R,K,D} = LazyTensorMappingComposition(s,t) 86 # Add check for matching sizes as a boundscheck
87 end
88 export TensorMappingComposition
85 89
86 # function range_size(tm::LazyTensorMappingComposition{T,R,K,D}, domain_size::NTuple{D,Integer}) where {T,R,K,D} 90 range_size(tm::TensorMappingComposition) = range_size(tm.t1)
87 # range_size(tm.t1, domain_size(tm.t2, domain_size)) 91 domain_size(tm::TensorMappingComposition) = domain_size(tm.t2)
88 # end
89 92
90 # function domain_size(tm::LazyTensorMappingComposition{T,R,K,D}, range_size::NTuple{R,Integer}) where {T,R,K,D} 93 function apply(c::TensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::Vararg{S,R} where S) where {T,R,K,D}
91 # domain_size(tm.t1, domain_size(tm.t2, range_size)) 94 apply(c.t1, LazyTensorMappingApplication(c.t2,v), I...)
92 # end 95 end
93 96
94 # function apply(c::LazyTensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::NTuple{R,Int}) where {T,R,K,D} 97 function apply_transpose(c::TensorMappingComposition{T,R,K,D}, v::AbstractArray{T,R}, I::Vararg{S,D} where S) where {T,R,K,D}
95 # apply(c.t1, LazyTensorMappingApplication(c.t2,v), I...) 98 apply_transpose(c.t2, LazyTensorMappingApplication(c.t1',v), I...)
96 # end 99 end
97 100
98 # function apply_transpose(c::LazyTensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::NTuple{D,Int}) where {T,R,K,D} 101 Base.:∘(s::TensorMapping, t::TensorMapping) = TensorMappingComposition(s,t)
99 # apply_transpose(c.t2, LazyTensorMappingApplication(c.t1',v), I...)
100 # end
101 102
102 # # Have i gone too crazy with the type parameters? Maybe they aren't all needed?
103
104 # export →
105 """ 103 """
106 LazyLinearMap{T,R,D,...}(A, range_indicies, domain_indicies) 104 LazyLinearMap{T,R,D,...}(A, range_indicies, domain_indicies)
107 105
108 TensorMapping defined by the AbstractArray A. `range_indicies` and `domain_indicies` define which indicies of A should 106 TensorMapping defined by the AbstractArray A. `range_indicies` and `domain_indicies` define which indicies of A should
109 be considerd the range and domain of the TensorMapping. Each set of indices must be ordered in ascending order. 107 be considerd the range and domain of the TensorMapping. Each set of indices must be ordered in ascending order.