@@ -87,17 +87,20 @@ class BatchGenerator:
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A dictionary specifying the size of the inputs in each dimension,
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e.g. ``{'lat': 30, 'lon': 30}``
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These are the dimensions the ML library will see. All other dimensions
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- will be stacked into one dimension called ``batch ``.
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+ will be stacked into one dimension called ``sample ``.
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input_overlap : dict, optional
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A dictionary specifying the overlap along each dimension
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e.g. ``{'lat': 3, 'lon': 3}``
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batch_dims : dict, optional
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A dictionary specifying the size of the batch along each dimension
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- e.g. ``{'time': 10}``. These will always be interated over.
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+ e.g. ``{'time': 10}``. These will always be iterated over.
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concat_input_dims : bool, optional
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If ``True``, the dimension chunks specified in ``input_dims`` will be
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- concatenated and stacked into the batch dimension. If ``False``, they
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- will be iterated over.
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+ concatenated and stacked into the ``sample`` dimension. The batch index
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+ will be included as a new level ``input_batch`` in the ``sample``
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+ coordinate.
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+ If ``False``, the dimension chunks specified in ``input_dims`` will be
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+ iterated over.
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preload_batch : bool, optional
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If ``True``, each batch will be loaded into memory before reshaping /
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processing, triggering any dask arrays to be computed.
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