fix: beta to f32

Author: prbzrg

benchmark/benchmarks.jl

@@ -10,8 +10,9 @@ import ADTypes,
 
 ndata = 2^10
 ndimensions = 1
-data_dist = Distributions.Beta(2.0f0, 4.0f0)
+data_dist = Distributions.Beta{Float32}(2.0f0, 4.0f0)
 r = rand(data_dist, ndimensions, ndata)
+r = convert.(Float32, r)
 
 nvariables = size(r, 1)
 icnf = ContinuousNormalizingFlows.ICNF(; nvariables)

examples/usage.jl

@@ -6,8 +6,9 @@ global_logger(TerminalLogger())
 using Distributions
 ndata = 1024
 ndimensions = 1
-data_dist = Beta(2.0f0, 4.0f0)
+data_dist = Beta{Float32}(2.0f0, 4.0f0)
 r = rand(data_dist, ndimensions, ndata)
+r = convert.(Float32, r)
 
 ## Parameters
 nvariables = size(r, 1)

test/ci_tests/regression_tests.jl

@@ -1,8 +1,9 @@
 Test.@testset verbose = true showtiming = true failfast = false "Regression Tests" begin
     ndata = 2^10
     ndimensions = 1
-    data_dist = Distributions.Beta(2.0f0, 4.0f0)
+    data_dist = Distributions.Beta{Float32}(2.0f0, 4.0f0)
     r = rand(data_dist, ndimensions, ndata)
+    r = convert.(Float32, r)
 
     nvariables = size(r, 1)
     icnf = ContinuousNormalizingFlows.ICNF(; nvariables)

test/ci_tests/smoke_tests.jl

@@ -9,14 +9,18 @@ Test.@testset verbose = true showtiming = true failfast = false "Smoke Tests" be
 
         ndata = 4
         ndimensions = 2
-        data_dist = Distributions.Beta(2.0f0, 4.0f0)
-        data_dist2 = Distributions.Beta(2.0f0, 4.0f0)
+        data_dist = Distributions.Beta{Float32}(2.0f0, 4.0f0)
+        data_dist2 = Distributions.Beta{Float32}(2.0f0, 4.0f0)
         if compute_mode isa ContinuousNormalizingFlows.VectorMode
             r = rand(data_dist, ndimensions)
+            r = convert.(Float32, r)
             r2 = rand(data_dist2, ndimensions)
+            r2 = convert.(Float32, r2)
         elseif compute_mode isa ContinuousNormalizingFlows.MatrixMode
             r = rand(data_dist, ndimensions, ndata)
+            r = convert.(Float32, r)
             r2 = rand(data_dist2, ndimensions, ndata)
+            r2 = convert.(Float32, r2)
         end
         df = DataFrames.DataFrame(permutedims(r), :auto)
         df2 = DataFrames.DataFrame(permutedims(r2), :auto)
@@ -124,7 +128,6 @@ Test.@testset verbose = true showtiming = true failfast = false "Smoke Tests" be
 
         Test.@testset verbose = true showtiming = true failfast = false "$adtype on loss" for adtype in
                                                                                               adtypes
-
             Test.@test !isnothing(DifferentiationInterface.gradient(diff_loss, adtype, ps))
             Test.@test !isnothing(DifferentiationInterface.gradient(diff2_loss, adtype, r))
 

test/quality_tests/checkby_JET_tests.jl

@@ -13,14 +13,18 @@ Test.@testset verbose = true showtiming = true failfast = false "CheckByJET" beg
 
         ndata = 4
         ndimensions = 2
-        data_dist = Distributions.Beta(2.0f0, 4.0f0)
-        data_dist2 = Distributions.Beta(2.0f0, 4.0f0)
+        data_dist = Distributions.Beta{Float32}(2.0f0, 4.0f0)
+        data_dist2 = Distributions.Beta{Float32}(2.0f0, 4.0f0)
         if compute_mode isa ContinuousNormalizingFlows.VectorMode
             r = rand(data_dist, ndimensions)
+            r = convert.(Float32, r)
             r2 = rand(data_dist2, ndimensions)
+            r2 = convert.(Float32, r2)
         elseif compute_mode isa ContinuousNormalizingFlows.MatrixMode
             r = rand(data_dist, ndimensions, ndata)
+            r = convert.(Float32, r)
             r2 = rand(data_dist2, ndimensions, ndata)
+            r2 = convert.(Float32, r2)
         end
         nvariables = size(r, 1)