👨‍🔧 Zero dropout and deep copy

FluxML · Dec 29, 2024 · 4ce351e · 4ce351e
1 parent 0d738d3
commit 4ce351e
Showing 1 changed file with 9 additions and 5 deletions.
diff --git a/test/entity_embedding.jl b/test/entity_embedding.jl
@@ -187,10 +187,13 @@ end
         3 4
     ])
 
+    stable_rng=StableRNG(123)
+
     for j in eachindex(embedding_dims)
         for i in eachindex(models)
+            # Without lightweight wrapper
             clf = models[1](
-                builder = MLJFlux.Short(n_hidden = 5, dropout = 0.2),
+                builder = MLJFlux.Short(n_hidden = 5, dropout = 0.0),
                 optimiser = Optimisers.Adam(0.01),
                 batch_size = 8,
                 epochs = 100,
@@ -199,13 +202,14 @@ end
                 embedding_dims = embedding_dims[3],
                 rng=42
             )
-            emb = MLJFlux.EntityEmbedder(clf)
-            mach_emb = machine(emb, X, ys[1])
             mach = machine(clf, X, ys[1])
-
             fit!(mach, verbosity = 0)
-            fit!(mach_emb, verbosity = 0)
             Xnew = transform(mach, X)
+            # With lightweight wrapper
+            clf2 = deepcopy(clf)
+            emb = MLJFlux.EntityEmbedder(clf2)
+            mach_emb = machine(emb, X, ys[1])
+            fit!(mach_emb, verbosity = 0)
             Xnew_emb = transform(mach_emb, X)
             @test Xnew == Xnew_emb