def test_overridable_args(model, optimizer, train_with_fp_copy):
model_copy = deepcopy(model)
conv_override = OrderedDict([(acts_key, 8), (wts_key, 8), (bias_key, 32), ('prop', 123), ('unexpetcted_prop', 456)])
overrides = OrderedDict([('conv1', conv_override)])
q = DummyQuantizer(model_copy, optimizer=optimizer, overrides=overrides, train_with_fp_copy=train_with_fp_copy)
pytest_raises_wrapper(TypeError, 'Expecting TypeError when overrides contains unexpected args', q.prepare_model)
model_copy = deepcopy(model)
relu_override = OrderedDict([(acts_key, 8), (wts_key, None), (bias_key, None),
('overridable_prop', 123), ('unexpetcted_prop', 456)])
overrides = OrderedDict([('relu1', relu_override)])
q = DummyQuantizer(model_copy, optimizer=optimizer, overrides=overrides, train_with_fp_copy=train_with_fp_copy)
pytest_raises_wrapper(TypeError, 'Expecting TypeError when overrides contains unexpected args', q.prepare_model)
model_copy = deepcopy(model)
conv_override = OrderedDict([(acts_key, 8), (wts_key, 8), (bias_key, 32), ('prop', 123)])
overrides = OrderedDict([('conv1', conv_override)])
q = DummyQuantizer(model_copy, optimizer=optimizer, overrides=overrides, train_with_fp_copy=train_with_fp_copy)
q.prepare_model()
assert model_copy.conv1.prop == 123
model_copy = deepcopy(model)
relu_override = OrderedDict([(acts_key, 8), (wts_key, None), (bias_key, None),
('overridable_prop', 123)])
overrides = OrderedDict([('relu1', relu_override)])
q = DummyQuantizer(model_copy, optimizer=optimizer, overrides=overrides, train_with_fp_copy=train_with_fp_copy)
q.prepare_model()
assert model_copy.relu1.overridable_prop == 123
def test_overrides_ordered_dict(model):
pytest_raises_wrapper(
TypeError,
'Expecting TypeError when overrides is not an OrderedDict',
DummyQuantizer,
model,
overrides={'testing': {
'testing': '123'
}})
def test_get_tensor_mean_n_stds_min_max():
pytest_raises_wrapper(ValueError,
'Expecting ValueError with n_stds = 0',
qu.get_tensor_mean_n_stds_min_max,
test_tensor,
n_stds=0)
mean = torch.tensor(-16.)
std = torch.tensor(62.87447738647461)
t_min, t_max = qu.get_tensor_mean_n_stds_min_max(test_tensor)
torch.testing.assert_allclose(t_min, mean - std)
torch.testing.assert_allclose(t_max, mean + std)
t_min, t_max = qu.get_tensor_mean_n_stds_min_max(test_tensor, n_stds=2)
torch.testing.assert_allclose(t_min, torch.tensor(-95.))
torch.testing.assert_allclose(t_max, torch.tensor(87.))
def test_get_tensor_avg_max_abs():
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_avg_max_abs,
test_tensor_2d,
across_dim=2)
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_avg_max_abs,
test_tensor_2d,
across_dim=6)
t_abs = qu.get_tensor_avg_max_abs(test_tensor_2d)
assert torch.equal(t_abs, torch.tensor(95.))
t_abs = qu.get_tensor_avg_max_abs(test_tensor_2d, across_dim=0)
assert torch.equal(t_abs, torch.tensor(83.))
t_abs = qu.get_tensor_avg_max_abs(test_tensor_4d, across_dim=0)
assert torch.equal(t_abs, torch.tensor(94.5))
def test_get_tensor_max_abs():
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_max_abs,
test_tensor_2d,
per_dim=2)
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_max_abs,
test_tensor_2d,
per_dim=6)
t_abs = qu.get_tensor_max_abs(test_tensor_4d)
assert torch.equal(t_abs, torch.tensor(95.))
t_abs = qu.get_tensor_max_abs(test_tensor_4d, per_dim=0)
assert torch.equal(t_abs, torch.tensor([94., 95.]))
t_abs = qu.get_tensor_max_abs(test_tensor_2d, per_dim=0)
assert torch.equal(t_abs, torch.tensor([93., 94., 87., 86., 83., 95.]))
def test_get_tensor_avg_min_max():
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_avg_min_max,
test_tensor_2d,
across_dim=2)
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_avg_min_max,
test_tensor_2d,
across_dim=6)
t_min, t_max = qu.get_tensor_avg_min_max(test_tensor_2d)
assert torch.equal(t_min, torch.tensor(-95.))
assert torch.equal(t_max, torch.tensor(87.))
t_min, t_max = qu.get_tensor_avg_min_max(test_tensor_2d, across_dim=0)
assert torch.equal(t_min, torch.tensor(-83.))
assert torch.equal(t_max, torch.tensor(72.))
t_min, t_max = qu.get_tensor_avg_min_max(test_tensor_4d, across_dim=0)
assert torch.equal(t_min, torch.tensor(-94.5))
assert torch.equal(t_max, torch.tensor(85.))
def test_get_tensor_min_max():
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_min_max,
test_tensor_2d,
per_dim=2)
pytest_raises_wrapper(ValueError,
too_large_dim_msg,
qu.get_tensor_min_max,
test_tensor_2d,
per_dim=6)
t_min, t_max = qu.get_tensor_min_max(test_tensor_4d)
assert torch.equal(t_min, torch.tensor(-95.))
assert torch.equal(t_max, torch.tensor(87.))
t_min, t_max = qu.get_tensor_min_max(test_tensor_4d, per_dim=0)
assert torch.equal(t_min, torch.tensor([-94., -95.]))
assert torch.equal(t_max, torch.tensor([87., 83.]))
t_min, t_max = qu.get_tensor_min_max(test_tensor_2d, per_dim=0)
assert torch.equal(t_min,
torch.tensor([-93., -94., -56., -86., -74., -95.]))
assert torch.equal(t_max, torch.tensor([33., 79., 87., 81., 83., 69.]))