def METHOD_NAME(tmpdir_factory):
    lt_ctx = Context(executor=InlineJobExecutor())
    datadir = tmpdir_factory.mktemp('hdf5_chunked_data')
    filename = os.path.join(datadir, 'chunked.emd')
    chunks = (32, 32, 128, 128)
    with h5py.File(filename, mode="w") as f:
        f.attrs.create('version_major', 0)
        f.attrs.create('version_minor', 2)
        f.create_group('experimental/science_data')
        group = f['experimental/science_data']
        group.attrs.create('emd_group_type', 1)
        data = np.ones((256, 256, 128, 128), dtype=np.float32)
        group.create_dataset(name='data', data=data, chunks=chunks)
        group.create_dataset(name='dim1', data=range(256))
        group['dim1'].attrs.create('name', b'dim1')
        group['dim1'].attrs.create('units', b'units1')
        group.create_dataset(name='dim2', data=range(256))
        group['dim2'].attrs.create('name', b'dim2')
        group['dim2'].attrs.create('units', b'units2')
        group.create_dataset(name='dim3', data=range(128))
        group['dim3'].attrs.create('name', b'dim3')
        group['dim3'].attrs.create('units', b'units3')
        group.create_dataset(name='dim4', data=range(128))
        group['dim4'].attrs.create('name', b'dim4')
        group['dim4'].attrs.create('units', b'units4')
        f.close()
    yield lt_ctx.load("auto", path=filename, ds_path="/experimental/science_data/data")