Merge pull request #12 from UM-Bridge/marlenaweidenauer-patch-1-1

delete zygote dependency in runtests.jl

Project.toml

@@ -7,13 +7,11 @@ version = "1.0.5"
 HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
-Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 HTTP = "1.0, 1.1, 1.2"
 JSON = "0.21"
 Parameters = "0.12"
-Zygote = "0.6"
 julia = "1"
 
 [extras]

test/runtests.jl

@@ -159,17 +159,14 @@ end
 
 end
 
-
-using Zygote  # For automatic differentiation
-
 # Define model for 1D function f(x) = x^2 that uses autodiff
 model = UMBridge.Model(
     name = "quadratic",
     inputSizes = [1],
     outputSizes = [1],
     supportsGradient = true,
     evaluate = (input, config) -> input[1]^2,
-    gradient = (outWrt, inWrt, input, sens, config) -> (Zygote.gradient(x -> x^2, input[1])[1] * sens[1])
+    gradient = (outWrt, inWrt, input, sens, config) -> 2*input[1][1] * sens[1]
 )
 
 function testserver_autodiff_gradient(models)
@@ -206,7 +203,7 @@ model = UMBridge.Model(
     outputSizes = [2],
     supportsJacobian = true,
     evaluate = (input, config) -> [input[1]^2, input[2]^2],
-    applyJacobian = (outWrt, inWrt, input, vec, config) -> Zygote.jacobian(x -> [x[1]^2, x[2]^2], input)[1] * vec
+    applyJacobian = (outWrt, inWrt, input, vec, config) -> [2*input[1][1] 0 ; 0 2*input[2][1]] * vec
 )
 
 function testserver_autodiff_jacobian(models)