# Buggy code
def generate(generator: DatasetGenerator, input) -> Dataset:
    """Generates dataset based on DatabaseGenerator class instance and iterable input
    For every element in input runs generators __call__ function.
    That function should return dict of numpy arrays containing single or multiple outputs for axis 0 of generating dataset
    """
    meta = _meta_preprocess(generator.meta())
    keys = sorted(meta.keys())
    tasks = [dask.delayed(_generate, nout=len(meta))(generator, i) for i in input]
    if len(tasks) == 0:
        return Dataset(
            {
                key: Tensor(
                    meta[key],
                    dask.array.from_array(np.empty(shape=(0,), dtype="uint8")),
                )
                for ki, key in enumerate(keys)
            }
        )

    return Dataset(
        {
            key: Tensor(
                meta[key],
                dask.array.concatenate(
                    [
                        dask.array.from_delayed(
                            task[ki],
                            shape=_dask_shape(meta[key]["shape"]),
                            dtype=meta[key]["dtype"],
                        )
                        for task in tasks
                    ]
                ),
                delayed_objs=[task[ki] for task in tasks],
            )
            for ki, key in enumerate(keys)
        }
    )


# Traceback (ValueError)
Traceback (most recent call last):
File "hub/compute/tests/test_transform.py", line 284, in <module>
test_threaded()
File "hub/compute/tests/test_transform.py", line 88, in test_threaded
create_classification_dataset(ds_init).store(
File "/Users/davitb/Git/Hub/hub/compute/transform.py", line 246, in store
ds = self.upload(results, url=url, token=token, progressbar=progressbar)
File "/Users/davitb/Git/Hub/hub/compute/transform.py", line 177, in upload
list(self.map(upload_chunk, index_batched_values))
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/pathos/threading.py", line 134, in map
return _pool.map(star(f), zip(*args)) # chunksize
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/multiprocess/pool.py", line 364, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/multiprocess/pool.py", line 771, in get
raise self._value
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/multiprocess/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/multiprocess/pool.py", line 48, in mapstar
return list(map(*args))
File "/Users/davitb/Library/Python/3.8/lib/python/site-packages/pathos/helpers/mp_helper.py", line 15, in <lambda>
func = lambda args: f(*args)
File "/Users/davitb/Git/Hub/hub/compute/transform.py", line 167, in upload_chunk
ds[key, i * length + k] = el
File "/Users/davitb/Git/Hub/hub/api/dataset.py", line 316, in __setitem__
self._tensors[subpath][slice_list] = value
File "/Users/davitb/Git/Hub/hub/store/dynamic_tensor.py", line 207, in __setitem__
self._dynamic_tensor[slice_[0]]
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 571, in __getitem__
return self.get_basic_selection(selection, fields=fields)
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 696, in get_basic_selection
return self._get_basic_selection_nd(selection=selection, out=out,
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 739, in _get_basic_selection_nd
return self._get_selection(indexer=indexer, out=out, fields=fields)
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 1028, in _get_selection
self._chunk_getitem(chunk_coords, chunk_selection, out, out_selection,
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 1649, in _chunk_getitem
self._process_chunk(out, cdata, chunk_selection, drop_axes,
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 1592, in _process_chunk
chunk = self._decode_chunk(cdata)
File "/usr/local/lib/python3.8/site-packages/zarr/core.py", line 1802, in _decode_chunk
chunk = chunk.reshape(self._chunks, order=self._order)
ValueError: cannot reshape array of size 0 into shape (50,3)

# Fixed code
def generate(generator: DatasetGenerator, input) -> Dataset:
    """Generates dataset based on DatabaseGenerator class instance and iterable input
    For every element in input runs generators __call__ function.
    That function should return dict of numpy arrays containing single or multiple outputs for axis 0 of generating dataset
    """
    if "dask" not in sys.modules:
        raise ModuleNotInstalledException("dask")
    else:
        import dask
        import dask.array

        global dask

    meta = _meta_preprocess(generator.meta())
    keys = sorted(meta.keys())

    tasks = [dask.delayed(_generate, nout=len(meta))(generator, i) for i in input]
    if len(tasks) == 0:
        return Dataset(
            {
                key: Tensor(
                    meta[key],
                    dask.array.from_array(np.empty(shape=(0,), dtype="uint8")),
                )
                for ki, key in enumerate(keys)
            }
        )

    return Dataset(
        {
            key: Tensor(
                meta[key],
                dask.array.concatenate(
                    [
                        dask.array.from_delayed(
                            task[ki],
                            shape=_dask_shape(meta[key]["shape"]),
                            dtype=meta[key]["dtype"],
                        )
                        for task in tasks
                    ]
                ),
                delayed_objs=[task[ki] for task in tasks],
            )
            for ki, key in enumerate(keys)
        }
    )