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# Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcv.cnn.bricks import HSigmoid
def test_hsigmoid():
# test assertion divisor can not be zero
with pytest.raises(AssertionError):
HSigmoid(divisor=0)
# test with default parameters
act = HSigmoid()
input_shape = torch.Size([1, 3, 64, 64])
input = torch.randn(input_shape)
output = act(input)
expected_output = torch.min(
torch.max((input + 3) / 6, torch.zeros(input_shape)),
torch.ones(input_shape))
# test output shape
assert output.shape == expected_output.shape
# test output value
assert torch.equal(output, expected_output)
# test with designated parameters
act = HSigmoid(1, 2, 0, 1)
input_shape = torch.Size([1, 3, 64, 64])
input = torch.randn(input_shape)
output = act(input)
expected_output = torch.min(
torch.max((input + 1) / 2, torch.zeros(input_shape)),
torch.ones(input_shape))
# test output shape
assert output.shape == expected_output.shape
# test output value
assert torch.equal(output, expected_output)
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