(self, indices, axis, out=None)
return OpTreeNode.build("onehot", None, None, idx=indices, axis=axis, out=out)
Generate optree for converting `indices` to a onehot representation.

        Arguments:
            indices (Tensor): Elements must be of numpy integer type for gpu
                              onehot to work.
            axis (int): the axis along the feature length dimension
            out (Tensor, optional): where the result will be stored. If out is
                                    None, only the op-tree will be returned.

        Returns:
            OpTreeNode: the resulting op-tree
Generate optree for converting `indices` to a onehot representation.
Generate optree for converting indices to a onehot representation .
def onehot(self, indices, axis, out=None):
        """
        Generate optree for converting `indices` to a onehot representation.

        Arguments:
            indices (Tensor): Elements must be of numpy integer type for gpu
                              onehot to work.
            axis (int): the axis along the feature length dimension
            out (Tensor, optional): where the result will be stored. If out is
                                    None, only the op-tree will be returned.

        Returns:
            OpTreeNode: the resulting op-tree
        """
        if axis not in (0, 1):
            raise ValueError("bad axis for onehot")
        assert (indices.dtype in [np.dtype(np.int32), np.dtype(np.uint32)]), "onehot indices " \
            "should be int32 or uint32, got " + str(indices.dtype)
        return OpTreeNode.build("onehot", None, None, idx=indices, axis=axis, out=out)
def onehot ( self , indices , axis , out = None ) : if axis not in ( 0 , 1 ) : raise ValueError ( "bad axis for onehot" ) assert ( indices . dtype in [ np . dtype ( np . int32 ) , np . dtype ( np . uint32 ) ] ) , "onehot indices " "should be int32 or uint32, got " + str ( indices . dtype ) return OpTreeNode . build ( "onehot" , None , None , idx = indices , axis = axis , out = out )