Towards Julia 1.6

Project.toml

@@ -1,13 +1,12 @@
 name = "Rayuela"
 uuid = "84bd14ec-51ef-568a-9c69-e494d1752004"
-author = ["Julieta Martinez <[email protected]>"]
+author = ["Julieta Martinez <[email protected]>"]
 version = "0.0.0"
 
 [deps]
 BinDeps = "9e28174c-4ba2-5203-b857-d8d62c4213ee"
-CUDAdrv = "c5f51814-7f29-56b8-a69c-e4d8f6be1fde"
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
-CuArrays = "3a865a2d-5b23-5a0f-bc46-62713ec82fae"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
@@ -22,6 +21,9 @@ SharedArrays = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
+[compat]
+julia = "1.6.2"
+
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 

README.md

@@ -46,37 +46,10 @@ The code in this package was written by
 
 ## Requirements
 
-This package is written in [Julia](https://github.com/JuliaLang/julia) 1.0, with some extension in C++ and CUDA.
+This package is written in [Julia](https://github.com/JuliaLang/julia) 1.6, with some extension in C++ and CUDA.
 You also need a CUDA-ready GPU. We have tested this code on an Nvidia Titan Xp GPU.
 
-## Installing
-
-Before all else, make sure that you have the `g++` compiler available from the command line, and the `nvcc` compiler availible at path `/usr/local/cuda/bin/nvcc`.
-
-Then, open julia and type `]` to enter Package mode:
-
-```julia
-julia>
-(v1.0) pkg>
-```
-
-Now you can clone our repo:
-
-```julia
-(v1.0) pkg> develop https://github.com/una-dinosauria/Rayuela.jl.git
-```
-
-This should put our code under `~/.julia/dev/Rayuela`.
-
-Due to an [open bug](https://github.com/JuliaLang/Pkg.jl/issues/465) with the package manager, you have to manually
-pull the latest changes:
-
-```bash
-cd ~/.julia/dev/Rayuela
-git pull
-```
-
-## Demo and data
+## Data and experiment setup
 
 You may explore the library with `SIFT1M`, a classical retrieval dataset:
 
@@ -94,24 +67,48 @@ Also make a directory for the results
 ```
 mkdir -p results/sift1m
 ```
+## Installing
+
+Before all else, make sure that you have the `g++` compiler available from the command line, and the `nvcc` compiler availible at path `/usr/local/cuda/bin/nvcc`.
+
+Clone this repo
+```bash
+git clone [email protected]:una-dinosauria/Rayuela.jl.git
+```
+
+Then, open julia and type `]` to enter Package mode:
+
+```julia
+julia>
+(@v1.6) pkg>
+```
+
+Now you can activate this repo:
+
+```julia
+(@v1.6) pkg> activate .
+(Rayuela) pkg>
+```
+
+This should load the relevant dependencies into your environment
 
-Finally, run the demo:
+Now you can run the demo:
 
 ```julia
-julia> include("~/.julia/dev/Rayuela/demos/demos_train_query_base.jl")
+julia> include("./demos/demos_train_query_base.jl")
 ```
 
 For query/base/protocol (example by default runs on SIFT1M), or
 
 ```julia
-julia> include("~/.julia/dev/Rayuela/demos/demos_query_base.jl")
+julia> include("./demos/demos_query_base.jl")
 ```
 
 For query/base protocol (example by default runs on LabelMe22K)
 
 This will showcase PQ, OPQ, RVQ, ERVQ, ChainQ and LSQ/LSQ++ (SR-C and SR-D).
 
-The rest of the datasets used in our ECCV'18 publication can be found on [gdrive](https://drive.google.com/drive/folders/1MnJLHpg5LP6pPQxQuL0VjnM03vHPvgP1?usp=sharing).
+The rest of the datasets used in our ECCV'18 publication can be found at [gdrive](https://drive.google.com/drive/folders/1MnJLHpg5LP6pPQxQuL0VjnM03vHPvgP1?usp=sharing).
 
 ## Roadmap
 

demos/demos_train_query_base.jl

@@ -8,7 +8,7 @@ include("experiment_utils.jl")
 # === experiment functions ===
 function run_demos(
   dataset_name="SIFT1M",
-  ntrain::Integer=Int(1e5),
+  ntrain::Integer=Int(1e4),
   m::Integer=8, h::Integer=256, niter::Integer=25)
 
   nquery, nbase, knn = 0, 0, 0

deps/build.jl

@@ -2,12 +2,13 @@ using BinDeps
 
 @BinDeps.setup
 
-cudautils   = library_dependency("cudautils")
+# cudautils   = library_dependency("cudautils")
 linscan_aqd = library_dependency("linscan_aqd", aliases=["linscan_aqd","linscan_aqd.so"])
 linscan_aqd_pairwise_byte = library_dependency("linscan_aqd_pairwise_byte", aliases=["linscan_aqd_pairwise_byte","linscan_aqd_pairwise_byte.so"])
 encode_icm_so = library_dependency("encode_icm_so", aliases=["encode_icm_so", "encode_icm_so.so"])
 
-deps = [cudautils, linscan_aqd, linscan_aqd_pairwise_byte, encode_icm_so]
+# deps = [cudautils, linscan_aqd, linscan_aqd_pairwise_byte, encode_icm_so]
+deps = [linscan_aqd, linscan_aqd_pairwise_byte, encode_icm_so]
 
 prefix=joinpath(BinDeps.depsdir(linscan_aqd))
 linscan_aqdbuilddir = joinpath(BinDeps.depsdir(linscan_aqd),"builds")
@@ -48,20 +49,24 @@ provides(BuildProcess,
         end
     end),encode_icm_so, os = :Unix, installed_libpath=joinpath(prefix,"builds"))
 
+@BinDeps.install Dict([(:linscan_aqd => :linscan_aqd),
+                      (:linscan_aqd_pairwise_byte => :linscan_aqd_pairwise_byte),
+                      (:encode_icm_so => :encode_icm_so)])
+
 # === CUDA code ===
-provides(BuildProcess,
-    (@build_steps begin
-        CreateDirectory(linscan_aqdbuilddir)
-        @build_steps begin
-            ChangeDirectory(linscan_aqdbuilddir)
-            FileRule(joinpath(prefix,"builds","cudautils.so"),@build_steps begin
-                `/usr/local/cuda/bin/nvcc -ptx ../src/cudautils.cu -o cudautils.ptx -arch=compute_35`
-                `/usr/local/cuda/bin/nvcc --shared -Xcompiler -fPIC -shared ../src/cudautils.cu -o cudautils.so -arch=compute_35`
-            end)
-        end
-    end),cudautils, os = :Unix, installed_libpath=joinpath(prefix,"builds"))
+# provides(BuildProcess,
+#     (@build_steps begin
+#         CreateDirectory(linscan_aqdbuilddir)
+#         @build_steps begin
+#             ChangeDirectory(linscan_aqdbuilddir)
+#             FileRule(joinpath(prefix,"builds","cudautils.so"),@build_steps begin
+#                 `/usr/local/cuda/bin/nvcc -ptx ../src/cudautils.cu -o cudautils.ptx -arch=compute_35`
+#                 `/usr/local/cuda/bin/nvcc --shared -Xcompiler -fPIC -shared ../src/cudautils.cu -o cudautils.so -arch=compute_35`
+#             end)
+#         end
+#     end),cudautils, os = :Unix, installed_libpath=joinpath(prefix,"builds"))
 
-@BinDeps.install Dict([(:linscan_aqd, :linscan_aqd),
-                      (:linscan_aqd_pairwise_byte, :linscan_aqd_pairwise_byte),
-                      (:encode_icm_so, :encode_icm_so),
-                      (:cudautils, :cudautils)])
+# @BinDeps.install Dict([(:linscan_aqd, :linscan_aqd),
+#                       (:linscan_aqd_pairwise_byte, :linscan_aqd_pairwise_byte),
+#                       (:encode_icm_so, :encode_icm_so),
+#                       (:cudautils, :cudautils)])

src/ChainQ.jl

@@ -386,7 +386,7 @@ function train_chainq(
   obj  = zeros(T, niter+1)
 
   # TODO expose these
-  use_cuda = true
+  use_cuda = false
   use_cpp = false
 
   CB = zeros(T, size(X))

src/ERVQ.jl

@@ -86,7 +86,7 @@ function train_ervq(
       weights = nothing  # use unweighted version of update_centers!
       to_update = zeros(Bool, h)
       to_update[B[j,:]] .= true # In. Whether a codebook entry needs update
-      cweights = zeros(Float64, h)   # Out. Cluster weights. We do not use this.
+      cweights = zeros(Int, h)   # Out. Cluster weights. We do not use this.
       Clustering.update_centers!(Xd, weights, B[j,:], to_update, C[j], cweights)
 
       # Check if some centres are unasigned

src/RVQ.jl

@@ -48,7 +48,7 @@ function quantize_rvq(
     # Create new codebook entries that we are missing
     if !isempty(unused)
       temp_codebook = similar(C[i]) # Out. The new codebooks will be added here
-      Clustering.repick_unused_centers(Xr, costs, temp_codebook, unused)
+      Clustering.repick_unused_centers(Xr, costs, temp_codebook, unused, Distances.SqEuclidean())
       singletons[i] = temp_codebook[:, unused]
     end
 

src/Rayuela.jl

@@ -13,8 +13,8 @@ using Distributed
 using Distributions
 
 # For LSQ encoding in the GPU
-using CUDAdrv
-using CuArrays
+# using CUDAdrv
+# using CuArrays
 
 using HDF5
 using LinearAlgebra
@@ -44,7 +44,7 @@ else
   error("Rayuela is not properly Installed.
   Please run Pkg.build(\"Rayuela\") and make sure you have nvcc and g++ available from the command line.")
 end
-cudautilsptx = cudautils[1:end-2] * "ptx"
+# cudautilsptx = cudautils[1:end-2] * "ptx"
 
 # === Functions to read data ===
 include("xvecs_read.jl")
@@ -74,8 +74,8 @@ include("LSQ.jl") # Local search quantization
 include("SR_perturbations.jl") # Utils for SR
 
 # === CUDA ports ===
-include("CudaUtilsModule.jl")
-include("SR.jl")  # Stochastic relaxations
-include("LSQ_GPU.jl") # Local search quantization
+# include("CudaUtilsModule.jl")
+# include("SR.jl")  # Stochastic relaxations
+# include("LSQ_GPU.jl") # Local search quantization
 
 end # module