Hello everyone,

I am looking on info on how to build a DataBlock with multiple pipelines at the same time. I have succesufully build a Block with 2 inputs and 1 target doing this: (thanks @muellerzr)

```
block=DataBlock(blocks = (ImageTupleBlock, TSBlock, TSBlock),
getters = [lambda t: t[0][0], lambda t: t[0][1], lambda t: t[1]],
splitter = IndexSplitter(val_idxs),
n_inp = 2)
```

but I would like to make `show_batch`

and `show_results`

work. The output I had using a custom class to wrap together `ImageTuple+TS`

was this:

Here a ImageTuple is shown at left and the timeseries at right. Stacking together the x timeseries and the y, similar to @takotab fastseq package.

This was done using a typed version of the

`show_batch`

method.
```
@typedispatch
def show_batch(x: ImageFeatureTuple, y: TSeries, samples, ctxs=None, max_n=10, nrows=None, figsize=None, fsteps=0, **kwargs):
"Show batch for TSeries objects"
if ctxs is None: _, ctxs = plt.subplots(min(len(samples), max_n) ,2, figsize=(10,3*len(samples)))
for b, tar, i in zip(samples.itemgot(0), samples.itemgot(1), range(max_n)):
b.show(ctx=ctxs[i], label='x (ghi)', bkgd=True)
tx=np.arange(fsteps, b[-1].shape[1]+fsteps)
tar.show(ctx=ctxs[i][1], label='y (ghi)', color='--*r', tx=tx, **kwargs)
return ctxs
```

I want a more elegant solution that is compatible with the rest of fastai and that works for my new 3 pipelines block. Probably I will need the bricolaging power of @sgugger here