extend contractor interface

src/contractor.jl

@@ -93,7 +93,16 @@ struct MpsParameters{S<:Real}
         iters_var = 1,
         Dtemp_multiplier = 2,
         method = :psvd_sparse,
-    ) where {S} = new(bond_dim, var_tol, num_sweeps, tol_SVD, iters_svd, iters_var, Dtemp_multiplier, method)
+    ) where {S} = new(
+        bond_dim,
+        var_tol,
+        num_sweeps,
+        tol_SVD,
+        iters_svd,
+        iters_var,
+        Dtemp_multiplier,
+        method,
+    )
 end
 
 """
@@ -186,6 +195,44 @@ mutable struct MpsContractor{T<:AbstractStrategy,R<:AbstractGauge,S<:Real} <:
     end
 end
 
+function MpsContractor(
+    ::Type{T},
+    ::Type{R},
+    ::Type{S},
+    net,
+    params;
+    beta::S,
+    graduate_truncation::Bool,
+    onGPU = true,
+    depth::Int = 0,
+) where {T, R, S}
+    return MpsContractor{T,R,S}(net, params; beta, graduate_truncation, onGPU, depth)
+end
+
+function MpsContractor(
+    ::Type{T},
+    ::Type{R},
+    net,
+    params;
+    beta::S,
+    graduate_truncation::Bool,
+    onGPU = true,
+    depth::Int = 0,
+) where {T, R, S}
+    return MpsContractor(T, R, S, net, params; beta, graduate_truncation, onGPU, depth)
+end
+
+function MpsContractor(
+    ::Type{T},
+    net,
+    params;
+    beta::S,
+    graduate_truncation::Bool,
+    onGPU = true,
+    depth::Int = 0,
+) where {T, S}
+    return MpsContractor(T, NoUpdate, net, params; beta, graduate_truncation, onGPU, depth)
+end
 """
 $(TYPEDSIGNATURES)
 Get the strategy used to contract the PEPS network.
@@ -243,10 +290,7 @@ Construct and memoize the top Matrix Product State (MPS) using Singular Value De
 
 This function constructs the top MPS using SVD for a given row in the PEPS network contraction. It recursively builds the MPS row by row, performing canonicalization, truncation, and compression steps as needed based on the specified parameters in `ctr.params`. The resulting MPS is memoized for efficient reuse.
 """
-@memoize Dict function mps_top(
-    ctr::MpsContractor{SVDTruncate,R,S},
-    i::Int,
-) where {R,S}
+@memoize Dict function mps_top(ctr::MpsContractor{SVDTruncate,R,S}, i::Int) where {R,S}
     Dcut = ctr.params.bond_dimension
     tolV = ctr.params.variational_tol
     tolS = ctr.params.tol_SVD
@@ -285,10 +329,7 @@ Construct and memoize the (bottom) Matrix Product State (MPS) using Singular Val
 
 This function constructs the (bottom) MPS using SVD for a given row in the PEPS network contraction. It recursively builds the MPS row by row, performing canonicalization, truncation, and compression steps as needed based on the specified parameters in `ctr.params`. The resulting MPS is memoized for efficient reuse.
 """
-@memoize Dict function mps(
-    ctr::MpsContractor{SVDTruncate,R,S},
-    i::Int,
-) where {R,S}
+@memoize Dict function mps(ctr::MpsContractor{SVDTruncate,R,S}, i::Int) where {R,S}
     Dcut = ctr.params.bond_dimension
     tolV = ctr.params.variational_tol
     tolS = ctr.params.tol_SVD
@@ -328,10 +369,7 @@ Construct and memoize the (bottom) Matrix Product State (MPS) approximation usin
 
 This function constructs the (bottom) MPS approximation using SVD for a given row in the PEPS network contraction. It recursively builds the MPS row by row, performing canonicalization, and truncation steps based on the specified parameters in `ctr.params`. The resulting MPS approximation is memoized for efficient reuse.
 """
-@memoize Dict function mps_approx(
-    ctr::MpsContractor{SVDTruncate,R,S},
-    i::Int,
-) where {R,S}
+@memoize Dict function mps_approx(ctr::MpsContractor{SVDTruncate,R,S}, i::Int) where {R,S}
     if i > ctr.peps.nrows
         W = mpo(ctr, ctr.layers.main, ctr.peps.nrows)
         return IdentityQMps(S, local_dims(W, :down); onGPU = ctr.onGPU) # F64 for now
@@ -370,10 +408,7 @@ Construct and memoize the top Matrix Product State (MPS) using the Zipper (trunc
 
 This function constructs the top Matrix Product State (MPS) using the Zipper (truncated Singular Value Decomposition) method for a given row in the PEPS network contraction. It recursively builds the MPS row by row, performing canonicalization, and truncation steps based on the specified parameters in `ctr.params`. The resulting MPS is memoized for efficient reuse.
 """
-@memoize Dict function mps_top(
-    ctr::MpsContractor{Zipper,R,S},
-    i::Int,
-) where {R,S}
+@memoize Dict function mps_top(ctr::MpsContractor{Zipper,R,S}, i::Int) where {R,S}
     Dcut = ctr.params.bond_dimension
     tolV = ctr.params.variational_tol
     tolS = ctr.params.tol_SVD
@@ -711,22 +746,14 @@ function sweep_gauges!(
 end
 
 
-function update_gauges!(
-    ctr::MpsContractor{T,S},
-    row::Site,
-    ::Val{:down},
-) where {T,S}
+function update_gauges!(ctr::MpsContractor{T,S}, row::Site, ::Val{:down}) where {T,S}
     for i ∈ 1:row-1
         sweep_gauges!(ctr, i)
     end
 end
 
 
-function update_gauges!(
-    ctr::MpsContractor{T,S},
-    row::Site,
-    ::Val{:up},
-) where {T,S}
+function update_gauges!(ctr::MpsContractor{T,S}, row::Site, ::Val{:up}) where {T,S}
     for i ∈ row-1:-1:1
         sweep_gauges!(ctr, i)
     end

test/runtests.jl

@@ -8,10 +8,13 @@ using LinearAlgebra
 using TensorCast
 using Statistics
 using MetaGraphs
+using CUDA
 
 disable_logging(LogLevel(1))
 
-onGPU = true
+user_onGPU = true  # or false, based on user's preference
+gpu_available = CUDA.functional()
+onGPU = user_onGPU && gpu_available
 
 using Test
 my_tests = []