cd keyword and up version

cossio · Sep 3, 2020 · 780790a · 780790a · cossio · Sep 3, 2020
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commit 780790a
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Showing 4 changed files with 6 additions and 6 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "RestrictedBoltzmannMachines"
 uuid = "12e6b396-7db5-4506-8cb6-664a4fe1e50e"
 authors = ["Jorge Fernandez-de-Cossio-Diaz <[email protected]>"]
-version = "0.2.5"
+version = "0.2.6"
 
 [deps]
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"

diff --git a/src/train/cd.jl b/src/train/cd.jl
@@ -16,13 +16,13 @@ end
 end
 
 """
-    train!(rbm, data, [cd])
+    train!(rbm, data)
 
 We measure training time in units of observations presented to the model.
 For example, if you want to train for 100 epochs, then set `iters = 100 * data.nobs`,
 where `data.nobs` is the number of observations in the dataset.
 """
-function train!(rbm::RBM, data::Data, cd::Union{CD,PCD} = PCD();
+function train!(rbm::RBM, data::Data; cd::Union{CD,PCD} = PCD(),
                 iters::Int, opt = ADAM(), ps::Params = params(rbm),
                 vm::AbstractArray = update_chains(rbm, cd, first(data).v), # Markov chains
                 history = nothing, # stores training history

diff --git a/test/profile/profiling.jl b/test/profile/profiling.jl
@@ -31,7 +31,7 @@ Profile.init(n=10^7, delay=0.01)
 @time train!(rbm, train_loader)
 @profiler train!(rbm, train_loader)
 
-train!(rbm, train_loader, PCD(1))
+train!(rbm, train_loader)
 #@descend train!(rbm, train_loader)
 first(train_loader)
 

diff --git a/test/rbm.jl b/test/rbm.jl
@@ -152,7 +152,7 @@ end
     gauge!(student)
     @test norm(teacher.weights) ≈ 1
     ps = params(student.weights)
-    train!(student, train_data, PCD(5); iters=10000 * 32, ps = ps, opt = Flux.ADAM())
+    train!(student, train_data; cd=PCD(5), iters=10000 * 32, ps = ps, opt = Flux.ADAM())
     @test norm(teacher.weights) ≈ 1
     @show dot(teacher.weights, student.weights)
     @test abs(dot(teacher.weights, student.weights)) ≥ 0.8
@@ -174,7 +174,7 @@ end
     gauge!(student)
     @test norm(teacher.weights) ≈ 1
     ps = params(student.weights)
-    train!(student, train_data, PCD(5); iters=10000 * 32, ps = ps, opt = Flux.ADAM())
+    train!(student, train_data; cd=PCD(5), iters=10000 * 32, ps = ps, opt = Flux.ADAM())
     @test norm(teacher.weights) ≈ 1
     @show dot(teacher.weights, student.weights)
     @test abs(dot(teacher.weights, student.weights)) ≥ 0.8