Hi all,

I’m trying to write an Automatic Differentiation example,

I get this error and I don’t know how to solve it.

```
ERROR: Need an adjoint for constructor Transpose{Float64,Array{Float64,2}}. Gradient is of type Array{Float64,2}
```

my original code is

```
using LinearAlgebra
using Zygote: gradient
function gaussian_log_likelihood(μ, σ, x)
"""
compute log-likelihood of x under N(μ,σ)
"""
ll = -1.0/2 * ((x-μ).*(x-μ)/(σ^2) .+ log(2*pi*σ^2))
return ll # log-likelihood function
end
function lr_model_nll(β,x,y;σ=1.)
return sum(-gaussian_log_likelihood(Transpose(x)*β, σ, y)) # Negative Log Likelihood
end
β_test = 0.6
σ_test = 0.3
x,y = ([3.45208 9.25217 4.81545], [7.03737, 17.9838, 10.1961])
ad_grad = gradient(β_test -> lr_model_nll(β_test,x,y;σ=σ_test), β_test)
# ...
```

The output of `lr_model_nll`

function is a scalar, so I don’t understand what’s the problem with this `gradient(β_test -> lr_model_nll(β_test,x,y;σ=σ_test), β_test)`

line of code.

Julia version is 1.0.4 (got it from official snap)

Flux v0.10.3, Zygote v0.4.9

Thank you so much in advance.