```
using Flux
function stacked_model(params, x)
y = x
for p in params
y = p(y)
end
return y
end
params = [Dense(10, 10, relu) for _ in 1:5]
x = rand(10)
y = stacked_model(params, x)
println(y)
```

## Option 1: Using a List of Parameters

In this option, we rewrite the jax model with stacked parameters using a list of parameters in Julia. We define a function called `stacked_model`

that takes in a list of parameters and an input `x`

. Inside the function, we iterate over each parameter in the list and apply it to the input `x`

. Finally, we return the output `y`

.

Here is the code:

```
using Flux
function stacked_model(params, x)
y = x
for p in params
y = p(y)
end
return y
end
params = [Dense(10, 10, relu) for _ in 1:5]
x = rand(10)
y = stacked_model(params, x)
println(y)
```

## Option 2: Using a Tuple of Parameters

In this option, we rewrite the jax model with stacked parameters using a tuple of parameters in Julia. We define a function called `stacked_model`

that takes in a tuple of parameters and an input `x`

. Inside the function, we iterate over each parameter in the tuple and apply it to the input `x`

. Finally, we return the output `y`

.

Here is the code:

```
using Flux
function stacked_model(params, x)
y = x
for p in params
y = p(y)
end
return y
end
params = (Dense(10, 10, relu), Dense(10, 10, relu), Dense(10, 10, relu), Dense(10, 10, relu), Dense(10, 10, relu))
x = rand(10)
y = stacked_model(params, x)
println(y)
```

## Option 3: Using Named Parameters

In this option, we rewrite the jax model with stacked parameters using named parameters in Julia. We define a function called `stacked_model`

that takes in named parameters and an input `x`

. Inside the function, we iterate over each parameter and apply it to the input `x`

. Finally, we return the output `y`

.

Here is the code:

```
using Flux
function stacked_model(;params, x)
y = x
for p in params
y = p(y)
end
return y
end
params = (layer1=Dense(10, 10, relu), layer2=Dense(10, 10, relu), layer3=Dense(10, 10, relu), layer4=Dense(10, 10, relu), layer5=Dense(10, 10, relu))
x = rand(10)
y = stacked_model(params=params, x=x)
println(y)
```

After analyzing the three options, the best option depends on the specific use case and personal preference. Option 1 using a list of parameters is the most straightforward and concise. Option 2 using a tuple of parameters provides a more structured approach. Option 3 using named parameters offers more flexibility and readability. It is recommended to choose the option that best suits the requirements and coding style of the project.