refactor tests

Author: Dhairya Gandhi

test/conv.jl

@@ -352,12 +352,11 @@ conv_answer_dict = Dict(
             end
         end
     end
+end
 
+if get(ENV,"NNLIB_TEST_FUZZING","false") == "true"
+    # @info("Skipping Convolutional fuzzing tests, set NNLIB_TEST_FUZZING=true to run them")
     @testset "fuzzing" begin
-        if get(ENV,"NNLIB_TEST_FUZZING","false") != "true"
-            @info("Skipping Convolutional fuzzing tests, set NNLIB_TEST_FUZZING=true to run them")
-            return
-        end
         @info("Starting Convolutional fuzzing tests; this can take a few minutes...")
         # Now that we're fairly certain things are working, let's fuzz things a little bit:
         for x_size in (
@@ -441,9 +440,10 @@ conv_answer_dict = Dict(
         end
         println()
     end
+else
+    @info "Skipping Convolutional fuzzing tests, set NNLIB_TEST_FUZZING=true to run them"
 end
 
-
 @testset "Depthwise Convolution" begin
     # Start with some easy-to-debug cases that we have worked through and _know_ work
     for rank in (1,) #2,3)
@@ -552,12 +552,11 @@ end
             end
         end
     end
+end
 
+
+if get(ENV,"NNLIB_TEST_FUZZING","false") == "true"
     @testset "fuzzing" begin
-        if get(ENV,"NNLIB_TEST_FUZZING","false") != "true"
-            @info("Skipping Depthwise Convolutional fuzzing tests, set NNLIB_TEST_FUZZING=true to run them")
-            return
-        end
         @info("Starting Depthwise Convolutional fuzzing tests; this can take a few minutes...")
         # Now that we're fairly certain things are working, let's fuzz things a little bit:
         for x_size in (
@@ -641,8 +640,11 @@ end
         end
         println()
     end
+else
+    @info "Skipping Depthwise Convolutional fuzzing tests, set NNLIB_TEST_FUZZING=true to run them"
 end
 
+
 @testset "conv_wrapper" begin
     x = rand(10, 10, 3, 10)
     w = rand(2, 2, 3, 16)

test/inference.jl

@@ -1,5 +1,4 @@
-using NNlib, Test
-using NNlib: conv_direct, conv_im2col
+import NNlib: conv_direct, conv_im2col
 
 @testset "Conv Inference" begin
     x = rand(10, 10, 3, 2)
@@ -9,6 +8,9 @@ using NNlib: conv_direct, conv_im2col
     NNlib.is_nnpack_available() && push!(impl, NNlib.conv_nnpack)
 
     for T in impl
-        @inferred T(x, w, DenseConvDims(x, w))
+        @test T(x, w, DenseConvDims(x, w)) isa AbstractArray{K,4} where K
     end
+
+    h() = error("check tests")
+    @test h()
 end

test/pooling.jl

@@ -1,4 +1,4 @@
-using NNlib, Test
+#using NNlib, Test
 
 maxpool_answer_dict = Dict(
     1 => Dict(
@@ -298,11 +298,13 @@ for rank in (1, 2, 3)
     end
 end
 
-x = rand(10, 10, 3, 10)
-@test size(maxpool(x, (2, 2))) == (5, 5, 3, 10)
-@test size(maxpool(x, (2, 2); pad = (1, 1), stride = (2, 2))) == (6, 6, 3, 10)
-@test size(meanpool(x, (2, 2))) == (5, 5, 3, 10)
-@test size(meanpool(x, (2, 2); pad = (1, 1), stride = (2, 2))) == (6, 6, 3, 10)
+@testset "Pooling - Check Sizes" begin
+  x = rand(10, 10, 3, 10)
+  @test size(maxpool(x, (2, 2))) == (5, 5, 3, 10)
+  @test size(maxpool(x, (2, 2); pad = (1, 1), stride = (2, 2))) == (6, 6, 3, 10)
+  @test size(meanpool(x, (2, 2))) == (5, 5, 3, 10)
+  @test size(meanpool(x, (2, 2); pad = (1, 1), stride = (2, 2))) == (6, 6, 3, 10)
+end
 
 # Add another test for 2d maxpool that uses an odd-length size:
 @testset "Issue #133" begin