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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 from_coo(cls, obj, vartype=None):
 """Deserialize a binary quadratic model from a COOrdinate_ format encoding. .. _COOrdinate: https://en.wikipedia.org/wiki/Sparse_matrix#Coordinate_list_(COO) Args: obj: (str/file):
 Either a string or a `.read()`-supporting `file object`_ that represents linear and quadratic biases for a binary quadratic model. This data is stored as a list of 3-tuples, (i, j, bias), where :math:`i=j` for linear biases. vartype (:class:`.Vartype`/str/set, optional):
 Variable type for the binary quadratic model. Accepted input values: * :class:`.Vartype.SPIN`, ``'SPIN'``, ``{-1, 1}`` * :class:`.Vartype.BINARY`, ``'BINARY'``, ``{0, 1}`` If not provided, the vartype must be specified with a header in the file. .. _file object: https://docs.python.org/3/glossary.html#term-file-object .. note:: Variables must use index lables (numeric lables). Binary quadratic models created from COOrdinate format encoding have offsets set to zero. Examples: An example of a binary quadratic model encoded in COOrdinate format. .. code-block:: none 0 0 0.50000 0 1 0.50000 1 1 -1.50000 The Coordinate format with a header .. code-block:: none # vartype=SPIN 0 0 0.50000 0 1 0.50000 1 1 -1.50000 This example saves a binary quadratic model to a COOrdinate-format file and creates a new model by reading the saved file. True """

        import dimod.serialization.coo as coo

        if isinstance(obj, str):
            return coo.loads(obj, cls=cls, vartype=vartype)

        return coo.load(obj, cls=cls, vartype=vartype)