code stringlengths 3 6.57k |
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test_same_on_batch(self, device, dtype) |
TestRandomMotionBlur(RandomGeneratorBaseTests) |
pytest.mark.parametrize('batch_size', [0, 1, 8]) |
pytest.mark.parametrize('kernel_size', [3, (3, 5) |
pytest.mark.parametrize('angle', [torch.tensor([10, 30]) |
pytest.mark.parametrize('direction', [torch.tensor([-1, -1]) |
torch.tensor([1, 1]) |
pytest.mark.parametrize('same_on_batch', [True, False]) |
test_valid_param_combinations(self, batch_size, kernel_size, angle, direction, same_on_batch, device, dtype) |
angle.to(device=device, dtype=dtype) |
direction.to(device=device, dtype=dtype) |
torch.tensor([30, 100]) |
torch.tensor([-1, 1]) |
torch.tensor([30, 100]) |
torch.tensor([-1, 1]) |
torch.tensor([30, 100]) |
torch.tensor([-1, 1]) |
torch.tensor([30, 100]) |
torch.tensor([-2, 1]) |
torch.tensor([30, 100]) |
torch.tensor([-1, 2]) |
test_invalid_param_combinations(self, kernel_size, angle, direction, device, dtype) |
pytest.raises(Exception) |
angle.to(device=device, dtype=dtype) |
direction.to(device=device, dtype=dtype) |
test_random_gen(self, device, dtype) |
torch.manual_seed(42) |
torch.tensor([30, 90]) |
torch.tensor([-1, 1]) |
angle.to(device=device, dtype=dtype) |
direction.to(device=device, dtype=dtype) |
torch.tensor([3, 3], device=device, dtype=torch.int32) |
torch.tensor([82.9362, 84.9002], device=device, dtype=dtype) |
torch.tensor([-0.2343, 0.9186], device=device, dtype=dtype) |
res.keys() |
expected.keys() |
assert_allclose(res['ksize_factor'], expected['ksize_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['angle_factor'], expected['angle_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['direction_factor'], expected['direction_factor'], rtol=1e-4, atol=1e-4) |
test_same_on_batch(self, device, dtype) |
torch.manual_seed(42) |
torch.tensor([30, 90]) |
torch.tensor([-1, 1]) |
angle.to(device=device, dtype=dtype) |
direction.to(device=device, dtype=dtype) |
torch.tensor([3, 3], device=device, dtype=torch.int32) |
torch.tensor([82.9362, 82.9362], device=device, dtype=dtype) |
torch.tensor([0.8300, 0.8300], device=device, dtype=dtype) |
res.keys() |
expected.keys() |
assert_allclose(res['ksize_factor'], expected['ksize_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['angle_factor'], expected['angle_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['direction_factor'], expected['direction_factor'], rtol=1e-4, atol=1e-4) |
TestRandomSolarizeGen(RandomGeneratorBaseTests) |
pytest.mark.parametrize('batch_size', [0, 1, 8]) |
pytest.mark.parametrize('thresholds', [torch.tensor([0, 1]) |
torch.tensor([0.4, 0.6]) |
pytest.mark.parametrize('additions', [torch.tensor([-0.5, 0.5]) |
pytest.mark.parametrize('same_on_batch', [True, False]) |
test_valid_param_combinations(self, batch_size, thresholds, additions, same_on_batch, device, dtype) |
thresholds.to(device=device, dtype=dtype) |
additions.to(device=device, dtype=dtype) |
torch.tensor([0, 2]) |
torch.tensor([-0.5, 0.5]) |
torch.tensor([-1, 1]) |
torch.tensor([-0.5, 0.5]) |
torch.tensor([-0.5, 0.5]) |
torch.tensor([0, 1]) |
torch.tensor([-0.5, 1]) |
torch.tensor([0, 1]) |
torch.tensor([-1, 0.5]) |
torch.tensor([0, 1]) |
test_invalid_param_combinations(self, thresholds, additions, device, dtype) |
pytest.raises(Exception) |
thresholds.to(device=device, dtype=dtype) |
additions.to(device=device, dtype=dtype) |
test_random_gen(self, device, dtype) |
torch.manual_seed(42) |
torch.tensor([0, 1], device=device, dtype=dtype) |
torch.tensor([-0.5, 0.5], device=device, dtype=dtype) |
res.keys() |
expected.keys() |
assert_allclose(res['thresholds_factor'], expected['thresholds_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['additions_factor'], expected['additions_factor'], rtol=1e-4, atol=1e-4) |
test_same_on_batch(self, device, dtype) |
torch.manual_seed(42) |
torch.tensor([0, 1], device=device, dtype=dtype) |
torch.tensor([-0.5, 0.5], device=device, dtype=dtype) |
res.keys() |
expected.keys() |
assert_allclose(res['thresholds_factor'], expected['thresholds_factor'], rtol=1e-4, atol=1e-4) |
assert_allclose(res['additions_factor'], expected['additions_factor'], rtol=1e-4, atol=1e-4) |
TestRandomPosterizeGen(RandomGeneratorBaseTests) |
pytest.mark.parametrize('batch_size', [0, 1, 8]) |
pytest.mark.parametrize('bits', [torch.tensor([0, 8]) |
pytest.mark.parametrize('same_on_batch', [True, False]) |
test_valid_param_combinations(self, batch_size, bits, same_on_batch, device, dtype) |
bits.to(device=device, dtype=dtype) |
torch.tensor([-1, 1]) |
torch.tensor([0, 9]) |
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