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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _resolve_dtype(data_type):
 """Retrieve the corresponding NumPy's `dtype` for a given data type."""

    if isinstance(data_type, _FIXED_ATOMIC):
        out = _get_atomic_dtype(data_type)
    elif isinstance(data_type, _FLEXIBLE_ATOMIC):
        out = (_get_atomic_dtype(data_type), data_type.length)
    elif isinstance(data_type, Array):
        shape = data_type.shape
        if isinstance(shape, _SEQUENCE_TYPES) and len(shape) == 1:
            # Workaround the exception `ValueError: invalid itemsize in
            # generic type tuple` when an `Array` of shape 0 or (0,) is nested
            # within another `Array`.
            shape = shape[0]

        out = (_resolve_dtype(data_type.element_type), shape)
    elif isinstance(data_type, Structure):
        out = [(field.name, _resolve_dtype(field.type))
               for field in data_type.fields]

    return out