# Batch evaluation for NeuralODE?

**URL:** <https://discourse.julialang.org/t/batch-evaluation-for-neuralode/66753>\
**Category:** Machine Learning\
**Created:** [August 20, 2021, 9:36pm UTC](https://discourse.julialang.org/t/batch-evaluation-for-neuralode/66753 "2021-08-20T21:36:03Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![kengyangyao](https://avatars.discourse-cdn.com/v4/letter/k/b5e925/32.png) [@kengyangyao](https://discourse.julialang.org/u/kengyangyao)\
**Post date:** [August 20, 2021, 9:36pm UTC](https://discourse.julialang.org/t/batch-evaluation-for-neuralode/66753/1 "2021-08-20T21:36:03Z")

</div>

Hi, I am new to Julia and am trying to use `NeuralODE` as follows:

```julia
d_in, dim_hidden = 25, 16
tspan = (0., 1.)
t = range(tspan[1], tspan[2], length=100)
dxdt = Chain(Dense(d_in, dim_hidden, tanh), Dense(dim_hidden, dim_hidden, tanh), Dense(dim_hidden, d_in,tanh))
n_ode = NeuralODE(dxdt, tspan, Tsit5(), saveat=t, reltol=1e-7, abstol=1e-9)

```

I found that when I pass a single array of shape (25, ), the model works OK:

```julia
tmp_in = rand(Float64, (25))
result = n_ode(tmp_in)

```

But if I pass a batch of arrays which has shape (115, 25), then it would not work:

```julia
tmp_in = rand(Float64, (115, 25))
result = n_ode(tmp_in)

```

and gives following error:

```julia
DimensionMismatch("A has dimensions (16,25) but B has dimensions (115,25)")

```

I guess it is more like a `Dense` layer issue, but am not exactly sure. Does anyone have idea how I should fix it? Thanks!

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [August 21, 2021, 1:26pm UTC](https://discourse.julialang.org/t/batch-evaluation-for-neuralode/66753/2 "2021-08-21T13:26:06Z")

</div>

It’s saying you’re multiplying a 16x25 matrix to a 115x25 matrix. Batches are columns, did you mean `tmp_in = rand(Float64, (25, 115))`?