From f76e00121487d4d6e40fd3d1a444b1b5481c8046 Mon Sep 17 00:00:00 2001
From: Dale Black <djblack@uci.edu>
Date: Tue, 25 Jun 2024 11:58:29 -0700
Subject: [PATCH] try new test approach for benchmark

---
 test/benchmarks.jl | 52 ----------------------------------------------
 test/runtests.jl   | 52 +++++++++++++++++++++++++++++++++++++++++++++-
 2 files changed, 51 insertions(+), 53 deletions(-)
 delete mode 100644 test/benchmarks.jl

diff --git a/test/benchmarks.jl b/test/benchmarks.jl
deleted file mode 100644
index 4c1768a..0000000
--- a/test/benchmarks.jl
+++ /dev/null
@@ -1,52 +0,0 @@
-using BenchmarkTools
-
-@testset "Benchmarks" begin
-    s = 10 # number of samples
-    e = 1 # number of evals
-
-    # Create an array of input sizes to benchmark for 2D
-    sizes_2D = [2^i for i in 3:4]
-
-    # Create DataFrames to store the benchmark results
-    df_dt_2D = DataFrame(
-        os_info = os_info,
-        gpu_info = gpu_info,
-        sizes = sizes_2D,
-        dt_proposed = Float64[]
-    )
-
-    for n in sizes_2D
-        f = Float32.(rand([0, 1], n, n))
-
-        if dev != Array
-            f_dev = dev(f)
-            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
-            push!(df_dt_2D, [os_info, gpu_info, n, minimum(dt).time])
-        end
-    end
-
-    # Create an array of input sizes to benchmark for 3D
-    sizes_3D = [2^i for i in 0:2]
-
-    # Create DataFrames to store the benchmark results
-    df_dt_3D = DataFrame(
-        os_info = os_info,
-        gpu_info = gpu_info,
-        sizes = sizes_3D,
-        dt_proposed = Float64[]
-    )
-
-    for n in sizes_3D
-        f = Float32.(rand([0, 1], n, n, n))
-
-        if dev != Array
-            f_dev = dev(f)
-            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
-            push!(df_dt_3D, [os_info, gpu_info, n, minimum(dt).time])
-        end
-    end
-
-    # Show the dataframes
-    @info df_dt_2D
-    @info df_dt_3D
-end
\ No newline at end of file
diff --git a/test/runtests.jl b/test/runtests.jl
index 78379dc..aee01b5 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -38,4 +38,54 @@ include("transform.jl")
 include("utils.jl")
 
 # Benchmark the transform function
-include("benchmarks.jl")
\ No newline at end of file
+@testset "Benchmarks" begin
+    s = 10 # number of samples
+    e = 1 # number of evals
+
+    # Create an array of input sizes to benchmark for 2D
+    sizes_2D = [2^i for i in 3:4]
+
+    # Create DataFrames to store the benchmark results
+    df_dt_2D = DataFrame(
+        os_info = os_info,
+        gpu_info = gpu_info,
+        sizes = sizes_2D,
+        dt_proposed = Float64[]
+    )
+
+    for n in sizes_2D
+        f = Float32.(rand([0, 1], n, n))
+
+        if dev != Array
+            f_dev = dev(f)
+            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
+            push!(df_dt_2D, [os_info, gpu_info, n, minimum(dt).time])
+        end
+    end
+
+    # Create an array of input sizes to benchmark for 3D
+    sizes_3D = [2^i for i in 0:2]
+
+    # Create DataFrames to store the benchmark results
+    df_dt_3D = DataFrame(
+        os_info = os_info,
+        gpu_info = gpu_info,
+        sizes = sizes_3D,
+        dt_proposed = Float64[]
+    )
+
+    for n in sizes_3D
+        f = Float32.(rand([0, 1], n, n, n))
+
+        if dev != Array
+            f_dev = dev(f)
+            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
+            push!(df_dt_3D, [os_info, gpu_info, n, minimum(dt).time])
+        end
+    end
+
+    # Show the dataframes
+    @info df_dt_2D
+    @info df_dt_3D
+    @test 1 == 1
+end
\ No newline at end of file