reformat

src/contractions/central.jl

@@ -83,7 +83,7 @@ function batched_mul!(
     sinter = sb * st * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2))
     if sl1 * sl2 * sr1 * sr2 < sinter
         # @cast E[(l1, l2), (r1, r2)] :=
-            # M.e11[l1, r1] * M.e21[l2, r1] * M.e12[l1, r2] * M.e22[l2, r2]
+        # M.e11[l1, r1] * M.e21[l2, r1] * M.e12[l1, r2] * M.e22[l2, r2]
         a11 = reshape(CuArray(M.e11), size(M.e11, 1), :, size(M.e11, 2))
         a21 = reshape(CuArray(M.e21), :, size(M.e21, 1), size(M.e21, 2))
         a12 = reshape(CuArray(M.e12), size(M.e12, 1), 1, 1, size(M.e12, 2))

src/contractions/dense.jl

@@ -192,7 +192,7 @@ end
 
 function contract_tensors43(B::Tensor{R,4}, A::Tensor{R,3}) where {R<:Real}
     # @matmul C[(x, y), (b, a), z] := sum(σ) B[y, z, a, σ] * A[x, b, σ]
-    @tensor C[x, y, b, a, z]:=B[y, z, a, σ] * A[x, b, σ]
+    @tensor C[x, y, b, a, z] := B[y, z, a, σ] * A[x, b, σ]
     C = reshape(C, size(C, 1) * size(C, 2), size(C, 3) * size(C, 4), size(C, 5))
     return C
 end

src/gauges.jl

@@ -30,7 +30,7 @@ function update_qr!(ψ::QMps{T}, AT::AbstractArray{T,3}, i::Site) where {T<:Real
     QT, RT = qr_fact(ATR)
     RT ./= maximum(abs.(RT))
     # @cast AT[x, σ, y] := QT[(x, σ), y] (σ ∈ 1:size(AT, 2))
-    AT = reshape(QT, size(QT, 1) ÷ size(AT, 2),  size(AT, 2), size(QT, 2))
+    AT = reshape(QT, size(QT, 1) ÷ size(AT, 2), size(AT, 2), size(QT, 2))
     ψ[i] = AT
     RT
 end

src/mps/canonise.jl

@@ -97,7 +97,7 @@ function _left_sweep!(
         R, Q = rq_fact(M, Dcut, tolS; toGPU = ψ.onGPU, kwargs...)
         R ./= maximum(abs.(R))
         # @cast B[x, σ, y] := Q[x, (σ, y)] (σ ∈ 1:size(B, 2))
-        B = reshape(Q, size(Q, 1),  size(B, 2), size(Q, 2) ÷ size(B, 2))
+        B = reshape(Q, size(Q, 1), size(B, 2), size(Q, 2) ÷ size(B, 2))
 
         ψ[i] = permutedims(B, (1, 3, 2))
     end

src/mps/utils.jl

@@ -42,8 +42,11 @@ end
 
 function is_left_normalized(ψ::QMps, ::Val{true})
     all(
-        eye(eltype(ψ), size(A, 2); toGPU = true) ≈
-        @tensor(Id[x, y] := A[α, x, σ] * A[α, y, σ]; backend=cuTENSOR, allocator=cuTENSOR) for A ∈ values(ψ.tensors) # TODO: split the line
+        eye(eltype(ψ), size(A, 2); toGPU = true) ≈ @tensor(
+            Id[x, y] := A[α, x, σ] * A[α, y, σ];
+            backend = cuTENSOR,
+            allocator = cuTENSOR
+        ) for A ∈ values(ψ.tensors) # TODO: split the line
     )
 end
 
@@ -59,8 +62,11 @@ end
 
 function is_right_normalized(ψ::QMps, ::Val{true})
     all(
-        eye(eltype(ψ), size(B, 1); toGPU = true) ≈
-        @tensor(Id[x, y] := B[x, α, σ] * B[y, α, σ]; backend=cuTENSOR, allocator=cuTENSOR) for B ∈ values(ψ.tensors) # TODO: split the line
+        eye(eltype(ψ), size(B, 1); toGPU = true) ≈ @tensor(
+            Id[x, y] := B[x, α, σ] * B[y, α, σ];
+            backend = cuTENSOR,
+            allocator = cuTENSOR
+        ) for B ∈ values(ψ.tensors) # TODO: split the line
     )
 end
 

src/zipper.jl

@@ -110,7 +110,7 @@ function zipper(
             CCC = reshape(CCC, size(CCC, 1), size(CCC, 2) ÷ s1, s1)
             C = permutedims(CCC, (2, 1, 3))
             # @cast V[x, y, z] := V[x, (y, z)] (z ∈ 1:s2)
-            V = reshape(V, size(V, 1), size(V, 2) ÷ s2,  s2)
+            V = reshape(V, size(V, 1), size(V, 2) ÷ s2, s2)
             out[i] = V
         else
             L = onGPU ? CUDA.ones(R, 1, 1, 1) : ones(R, 1, 1, 1)