Nested lists are zipped unexpectedly
MEMBER
Yes following the Tensorflow Datasets convention, objects with type `Sequence of a Dict` are actually stored as a `dictionary of lists`.
See the [documentation](https://huggingface.co/docs/datasets/features.html?highlight=features) for more details
2020-11-25T16:29:37Z
https://github.com/huggingface/datasets/issues/888#issuecomment-733813248
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2020-11-25T16:30:42Z
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CONTRIBUTOR
Thanks.
This is a bit (very) confusing, but I guess if its intended, I'll just work with it as if its how my data was originally structured :) 

2020-11-25T17:30:36Z
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I might misunderstand something, but I expect that if I define:
```python
"top": datasets.features.Sequence({
  "middle": datasets.features.Sequence({
    "bottom": datasets.Value("int32")
  })
})
```

And I then create an example:
```python
yield 1, {
  "top": [{
    "middle": [
      {"bottom": 1},
      {"bottom": 2}
    ]
  }]
}
```

I then load my dataset:
```python
train = load_dataset("my dataset")["train"]
```

and expect to be able to access `data[0]["top"][0]["middle"][0]`.

That is not the case. Here is `data[0]` as JSON:

```json
{"top": {"middle": [{"bottom": [1, 2]}]}}
```

Clearly different than the thing I inputted.
```json
{"top": [{"middle": [{"bottom": 1},{"bottom": 2}]}]}
```