def test_get_all_elections_xlsx(self):
        response = self.client.get(reverse('results-export'))

        self.assertEqual(response.status_code, 200)

        self.assertEqual(
            response['Content-Disposition'],
            'attachment; filename="Election Results.xlsx"'
        )

        wb = openpyxl.load_workbook(io.BytesIO(response.content))

        self.assertEqual(len(wb.worksheets), 2)

        # Check first worksheet.
        ws = wb.worksheets[0]

        self.assertEqual(wb.sheetnames[0], 'Election 0')

        row_count = ws.max_row
        col_count = ws.max_column
        self.assertEqual(row_count, 25)
        self.assertEqual(col_count, 5)

        self.assertEqual(str(ws.cell(1, 1).value), 'Election 0 Results')

        self.assertEqual(str(ws.cell(2, 1).value), 'Candidates')

        cellContents = [
            'Position 0',
            'Party 0',
            '0, 0',
            'Party 1',
            '3, 3',
            'Party 2',
            'None',
            'Position 1',
            'Party 0',
            '1, 1',
            'Party 1',
            '4, 4',
            'Party 2',
            'None',
            'Position 2',
            'Party 0',
            '2, 2',
            'Party 1',
            '5, 5',
            'Party 2',
            'None'
        ]
        for cellIndex, content in enumerate(cellContents, 5):
            self.assertEqual(str(ws.cell(cellIndex, 1).value), content) 

        self.assertEqual(str(ws.cell(2, 2).value), 'Number of Votes')

        self.assertEqual(str(ws.cell(3, 2).value), '0')

        self.assertEqual(str(ws.cell(4, 2).value), '0') # Section

        self.assertEqual(str(ws.cell(7, 2).value), '1')
        self.assertEqual(str(ws.cell(9, 2).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 2).value), '2')
        self.assertEqual(str(ws.cell(16, 2).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 2).value), '0')
        self.assertEqual(str(ws.cell(23, 2).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(4, 3).value), '1') # Section

        self.assertEqual(str(ws.cell(7, 3).value), '0')
        self.assertEqual(str(ws.cell(9, 3).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 3).value), '0')
        self.assertEqual(str(ws.cell(16, 3).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 3).value), '1')
        self.assertEqual(str(ws.cell(23, 3).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 4).value), '1')

        self.assertEqual(str(ws.cell(4, 4).value), '2') # Section

        self.assertEqual(str(ws.cell(7, 4).value), '0')
        self.assertEqual(str(ws.cell(9, 4).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 4).value), '0')
        self.assertEqual(str(ws.cell(16, 4).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 4).value), '0')
        self.assertEqual(str(ws.cell(23, 4).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 5).value), 'Total Votes')
        self.assertEqual(str(ws.cell(7, 5).value), '1')
        self.assertEqual(str(ws.cell(9, 5).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 5).value), '2')
        self.assertEqual(str(ws.cell(16, 5).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 5).value), '1')
        self.assertEqual(str(ws.cell(23, 5).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        # Check second worksheet.
        ws = wb.worksheets[1]

        self.assertEqual(wb.sheetnames[1], 'Election 1')

        row_count = ws.max_row
        col_count = ws.max_column
        self.assertEqual(row_count, 25)
        self.assertEqual(col_count, 5)

        self.assertEqual(str(ws.cell(1, 1).value), 'Election 1 Results')

        self.assertEqual(str(ws.cell(2, 1).value), 'Candidates')

        self.assertEqual(str(ws.cell(2, 1).value), 'Candidates')

        cellContents = [
            'Position 3',
            'Party 3',
            '6, 6',
            'Party 4',
            '9, 9',
            'Party 5',
            'None',
            'Position 4',
            'Party 3',
            '7, 7',
            'Party 4',
            '10, 10',
            'Party 5',
            'None',
            'Position 5',
            'Party 3',
            '8, 8',
            'Party 4',
            '11, 11',
            'Party 5',
            'None'
        ]
        for cellIndex, content in enumerate(cellContents, 5):
            self.assertEqual(str(ws.cell(cellIndex, 1).value), content) 

        self.assertEqual(str(ws.cell(2, 2).value), 'Number of Votes')

        self.assertEqual(str(ws.cell(3, 2).value), '2')

        self.assertEqual(str(ws.cell(4, 2).value), '3') # Section

        self.assertEqual(str(ws.cell(7, 2).value), '1')
        self.assertEqual(str(ws.cell(9, 2).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 2).value), '1')
        self.assertEqual(str(ws.cell(16, 2).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 2).value), '0')
        self.assertEqual(str(ws.cell(23, 2).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(4, 3).value), '4') # Section

        self.assertEqual(str(ws.cell(7, 3).value), '0')
        self.assertEqual(str(ws.cell(9, 3).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 3).value), '0')
        self.assertEqual(str(ws.cell(16, 3).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 3).value), '1')
        self.assertEqual(str(ws.cell(23, 3).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 4).value), '3')

        self.assertEqual(str(ws.cell(4, 4).value), '5') # Section

        self.assertEqual(str(ws.cell(7, 4).value), '0')
        self.assertEqual(str(ws.cell(9, 4).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 4).value), '0')
        self.assertEqual(str(ws.cell(16, 4).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 4).value), '0')
        self.assertEqual(str(ws.cell(23, 4).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 5).value), 'Total Votes')
        self.assertEqual(str(ws.cell(7, 5).value), '1')
        self.assertEqual(str(ws.cell(9, 5).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 5).value), '1')
        self.assertEqual(str(ws.cell(16, 5).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 5).value), '1')
        self.assertEqual(str(ws.cell(23, 5).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')
def get_attn(attn_type):
    if isinstance(attn_type, torch.nn.Module):
        return attn_type
    module_cls = None
    if attn_type is not None:
        if isinstance(attn_type, str):
            attn_type = attn_type.lower()
            # Lightweight attention modules (channel and/or coarse spatial).
            # Typically added to existing network architecture blocks in addition to existing convolutions.
            if attn_type == 'se':
                module_cls = SEModule
            elif attn_type == 'ese':
                module_cls = EffectiveSEModule
            elif attn_type == 'eca':
                module_cls = EcaModule
            elif attn_type == 'ecam':
                module_cls = partial(EcaModule, use_mlp=True)
            elif attn_type == 'ceca':
                module_cls = CecaModule
            elif attn_type == 'ge':
                module_cls = GatherExcite
            elif attn_type == 'gc':
                module_cls = GlobalContext
            elif attn_type == 'gca':
                module_cls = partial(GlobalContext, fuse_add=True, fuse_scale=False)
            elif attn_type == 'cbam':
                module_cls = CbamModule
            elif attn_type == 'lcbam':
                module_cls = LightCbamModule

            # Attention / attention-like modules w/ significant params
            # Typically replace some of the existing workhorse convs in a network architecture.
            # All of these accept a stride argument and can spatially downsample the input.
            elif attn_type == 'sk':
                module_cls = SelectiveKernel
            elif attn_type == 'splat':
                module_cls = SplitAttn

            # Self-attention / attention-like modules w/ significant compute and/or params
            # Typically replace some of the existing workhorse convs in a network architecture.
            # All of these accept a stride argument and can spatially downsample the input.
            elif attn_type == 'lambda':
                return LambdaLayer
            elif attn_type == 'bottleneck':
                return BottleneckAttn
            elif attn_type == 'halo':
                return HaloAttn
            elif attn_type == 'nl':
                module_cls = NonLocalAttn
            elif attn_type == 'bat':
                module_cls = BatNonLocalAttn

            # Woops!
            else:
                assert False, "Invalid attn module (%s)" % attn_type
        elif isinstance(attn_type, bool):
            if attn_type:
                module_cls = SEModule
        else:
            module_cls = attn_type
    return module_cls