updated tabular model, and added tests

Author: manikyabard

src/models/Models.jl

@@ -18,7 +18,7 @@ include("tabularmodel.jl")
 
 
 export xresnet18, xresnet50, UNetDynamic, 
-TabularModel, get_emb_sz, embeddingbackbone, continuousbackbone
+TabularModel, get_emb_sz, embeddingbackbone, continuousbackbone, sigmoidrange
 
 
 end

src/models/tabularmodel.jl

@@ -18,8 +18,12 @@ end
 # 	[_one_emb_sz(catdict, catcol, sz_dict) for catcol in cols]
 # end
 
-function embeddingbackbone(embedding_sizes, dropoutprob)
-    embedslist = [Embedding(ni, nf) for (ni, nf) in embedding_sizes]
+function sigmoidrange(x, low, high)
+	@. Flux.sigmoid(x) * (high - low) + low
+end
+
+function embeddingbackbone(embedding_sizes, dropoutprob=0.)
+    embedslist = [Embedding(ni => nf) for (ni, nf) in embedding_sizes]
     emb_drop = Dropout(dropoutprob)
     Chain(
         x -> tuple(eachrow(x)...), 
@@ -35,7 +39,7 @@ end
 function TabularModel(
         catbackbone,
         contbackbone,    
-        layers; 
+        layers=[200, 100]; 
         n_cat,
         n_cont,
         out_sz,

test/imports.jl

@@ -6,6 +6,7 @@ using FastAI: Image, Keypoints, Mask, testencoding, Label, OneHot, ProjectiveTra
     encodedblock, decodedblock, encode, decode, mockblock
 using FilePathsBase
 using FastAI.Datasets
+using FastAI.Models
 using DLPipelines
 import DataAugmentation
 import DataAugmentation: getbounds

test/models/tabularmodel.jl

@@ -0,0 +1,51 @@
+include("../imports.jl")
+
+@testset ExtendedTestSet "TabularModel Components" begin
+    @testset ExtendedTestSet "embeddingbackbone" begin
+        embed_szs = [(5, 10), (100, 30), (2, 30)]
+        embeds = embeddingbackbone(embed_szs, 0.)
+        x = [rand(1:n) for (n, _) in embed_szs]
+
+        @test size(embeds(x)) == (70, 1)
+    end
+
+    @testset ExtendedTestSet "continuousbackbone" begin
+        n = 5
+        contback = continuousbackbone(n)
+        x = rand(5, 1)
+        @test size(contback(x)) == (5, 1)
+    end
+
+    @testset ExtendedTestSet "TabularModel" begin
+        n = 5
+        embed_szs = [(5, 10), (100, 30), (2, 30)]
+        
+        embeds = embeddingbackbone(embed_szs, 0.)
+        contback = continuousbackbone(n)
+
+        tm = TabularModel(
+            embeds, 
+            contback, 
+            [200, 100],
+            n_cat=3,
+            n_cont=5,
+            out_sz=4
+        )
+        x = ([rand(1:n) for (n, _) in embed_szs], rand(5, 1))
+        @test size(tm(x)) == (4, 1)
+
+        tm2 = TabularModel(
+            embeds, 
+            contback, 
+            [200, 100],
+            n_cat=3,
+            n_cont=5,
+            out_sz=4,
+            final_activation=x->FastAI.sigmoidrange(x, 2, 5)
+        )
+        y2 = tm2(x)
+        @test all(y2.> 2) && all(y2.<5)
+    end
+end
+
+

test/runtests.jl

@@ -55,4 +55,10 @@ include("imports.jl")
         end
         # TODO: test learning rate finder
     end
+
+    @testset ExtendedTestSet "models/" begin
+        @testset ExtendedTestSet "tabularmodel.jl" begin
+            include("models/tabularmodel.jl")
+        end
+    end
 end