Test explicit calling syntax

Author: MilesCranmer

test/test_custom_operators.jl

@@ -21,7 +21,7 @@ tree = op1(op2(x1, x2), op3(x1))
 @test repr(tree) == "op1(op2(x1, x2), op3(x1))"
 # Test evaluation:
 X = randn(MersenneTwister(0), Float32, 2, 10);
-@test tree(X) ≈ ((x1, x2) -> op1(op2(x1, x2), op3(x1))).(X[1, :], X[2, :])
+@test tree(X, operators) ≈ ((x1, x2) -> op1(op2(x1, x2), op3(x1))).(X[1, :], X[2, :])
 
 # Now, test that we can work with operators defined in modules
 module A
@@ -47,7 +47,7 @@ function create_and_eval_tree()
     tree = my_func_a(my_func_a(x2, 0.2), my_func_b(x1))
     func = (x1, x2) -> my_func_a(my_func_a(x2, 0.2), my_func_b(x1))
     X = randn(MersenneTwister(0), 2, 20)
-    return tree(X), func.(X[1, :], X[2, :])
+    return tree(X, operators), func.(X[1, :], X[2, :])
 end
 
 end
@@ -74,4 +74,7 @@ c1 = Node(Float64; val=0.2)
 tree = my_func_c(my_func_c(x2, 0.2), my_func_d(x1))
 func = (x1, x2) -> my_func_c(my_func_c(x2, 0.2), my_func_d(x1))
 X = randn(MersenneTwister(0), 2, 20)
+@test tree(X, operators) ≈ func.(X[1, :], X[2, :])
+
+# Test deprecated implicit syntax:
 @test tree(X) ≈ func.(X[1, :], X[2, :])

test/test_derivatives.jl

@@ -88,12 +88,15 @@ for type in [Float16, Float32, Float64], turbo in [true, false]
                     i in 1:nfeatures
                 ],
             )'
-        predicted_grad3 = tree'(X)
+        predicted_grad3 = tree'(X, operators; turbo=turbo)
+        # Test deprecated syntax:
+        predicted_grad4 = tree'(X; turbo=turbo)
 
         # Print largest difference between predicted_grad, true_grad:
         @test array_test(predicted_grad, true_grad)
         @test array_test(predicted_grad2, true_grad)
         @test array_test(predicted_grad3, true_grad)
+        @test array_test(predicted_grad4, true_grad)
 
         # Make sure that the array_test actually works:
         @test !array_test(predicted_grad .* 0, true_grad)

test/test_error_handling.jl

@@ -1,6 +1,27 @@
 using DynamicExpressions
 using Test
 
+# Before defining OperatorEnum, calling the implicit (deprecated)
+# syntax should fail:
+tree = Node(; feature=1)
+try
+    tree([1.0 2.0]')
+    @test false
+catch e
+    @test isa(e, ErrorException)
+    expected_error_msg = "The `tree(X; kws...)` syntax is deprecated"
+    @test occursin(expected_error_msg, e.msg)
+end
+
+try
+    tree'([1.0 2.0]')
+    @test false
+catch e
+    @test isa(e, ErrorException)
+    expected_error_msg = "The `tree'(X; kws...)` syntax is deprecated"
+    @test occursin(expected_error_msg, e.msg)
+end
+
 # Test that we generate errors:
 baseT = Float64
 T = Union{baseT,Vector{baseT},Matrix{baseT}}
@@ -33,11 +54,11 @@ output, flag = eval_tree_array(
 
 # Default is to catch errors:
 try
-    tree([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+    tree([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], operators)
     @test false
 catch e
     @test isa(e, ErrorException)
 end
 
 # But can be overrided:
-output = tree([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]; throw_errors=false)
+output = tree([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], operators; throw_errors=false)

test/test_evaluation.jl

@@ -69,6 +69,9 @@ for turbo in [false, true],
 
     zero_tolerance = (T <: Union{Float16,Complex} ? 1e-4 : 1e-6)
     @test all(abs.(test_y .- true_y) / N .< zero_tolerance)
+
+    test_y_helper = tree(X, operators; turbo=turbo)
+    @test all(test_y .== test_y_helper)
 end
 
 for turbo in [false, true], T in [Float16, Float32, Float64, ComplexF32, ComplexF64]
@@ -110,7 +113,7 @@ for turbo in [false, true], T in [Float16, Float32, Float64, ComplexF32, Complex
     x1 = Node(T; feature=1)
     tree = sin(x1 / 0.0)
     X = randn(Float32, 3, 10)
-    @test isnan(tree(X; turbo=turbo)[1])
+    @test isnan(tree(X, operators; turbo=turbo)[1])
 end
 
 # Check if julia version >= 1.7:
@@ -124,7 +127,7 @@ if VERSION >= v"1.7"
     X = randn(Float32, 10)
     local stack
     try
-        tree(X)[1]
+        tree(X, operators)[1]
         @test false
     catch e
         @test e isa ErrorException
@@ -137,10 +140,10 @@ if VERSION >= v"1.7"
 
     # If a method is not defined, we should get a nothing:
     X = randn(Float32, 1, 10)
-    @test tree(X; throw_errors=false) === nothing
+    @test tree(X, operators; throw_errors=false) === nothing
     # or a MethodError:
     try
-        tree(X; throw_errors=true)
+        tree(X, operators; throw_errors=true)
         @test false
     catch e
         @test e isa ErrorException

test/test_generic_operators.jl

@@ -7,4 +7,4 @@ operators = GenericOperatorEnum(; binary_operators=(*,))
 
 x1, x2, x3 = [Node(String; feature=i) for i in 1:3]
 tree = x1 * " " * "World!"
-@test tree(["Hello"]) == "Hello World!"
+@test tree(["Hello"], operators) == "Hello World!"

test/test_tensor_operators.jl

@@ -17,19 +17,19 @@ X = [[2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]
 
 tree = Node(1, c1, x2)
 @test repr(tree) == "vec_add([1.0, 2.0, 3.0], x2)"
-@test tree(X) == [4.0, 5.0, 6.0]
+@test tree(X, operators) == [4.0, 5.0, 6.0]
 tree = Node(1, x1, c1)
 @test repr(tree) == "vec_add(x1, [1.0, 2.0, 3.0])"
-@test tree(X) == [3.0, 4.0, 5.0]
+@test tree(X, operators) == [3.0, 4.0, 5.0]
 
 # Try same things, but with constructors:
 @extend_operators operators
 tree = vec_add(c1, x2)
 @test repr(tree) == "vec_add([1.0, 2.0, 3.0], x2)"
-@test tree(X) == [4.0, 5.0, 6.0]
+@test tree(X, operators) == [4.0, 5.0, 6.0]
 tree = vec_add(x1, c1)
 @test repr(tree) == "vec_add(x1, [1.0, 2.0, 3.0])"
-@test tree(X) == [3.0, 4.0, 5.0]
+@test tree(X, operators) == [3.0, 4.0, 5.0]
 
 # Also test unary operators:
 function vec_square(x)
@@ -40,17 +40,17 @@ operators = GenericOperatorEnum(; binary_operators=[vec_add], unary_operators=[v
 @extend_operators operators
 tree = Node(1, c1)
 @test repr(tree) == "vec_square([1.0, 2.0, 3.0])"
-@test tree(X) == [1.0, 4.0, 9.0]
+@test tree(X, operators) == [1.0, 4.0, 9.0]
 @test vec_square(c1).val == [1.0, 4.0, 9.0]
 tree = Node(1, Node(1, c1), x1)
 @test repr(tree) == "vec_add(vec_square([1.0, 2.0, 3.0]), x1)"
-@test tree(X) == [3.0, 6.0, 11.0]
+@test tree(X, operators) == [3.0, 6.0, 11.0]
 @test (vec_add(vec_square(c1), x1))(X) == [3.0, 6.0, 11.0]
 
 # Also test mixed scalar and floats:
 c2 = Node(T; val=2.0)
 @test repr(c2) == "2.0"
 tree = Node(1, Node(1, c1, x1), c2)
 @test repr(tree) == "vec_add(vec_add([1.0, 2.0, 3.0], x1), 2.0)"
-tree(X)
-@test tree(X) == [5.0, 6.0, 7.0]
+tree(X, operators)
+@test tree(X, operators) == [5.0, 6.0, 7.0]