diff --git a/_typos.toml b/_typos.toml index 2310e314c242bb..a50d2e6253032e 100644 --- a/_typos.toml +++ b/_typos.toml @@ -105,7 +105,6 @@ expaned = 'expaned' epxand = 'epxand' Expexted = 'Expexted' expolitation = 'expolitation' -extream = 'extream' faild = 'faild' Flase = 'Flase' featue = 'featue' diff --git a/test/deprecated/legacy_test/test_bfgs_deprecated.py b/test/deprecated/legacy_test/test_bfgs_deprecated.py index e709eca7ab6225..3002f47a10e865 100644 --- a/test/deprecated/legacy_test/test_bfgs_deprecated.py +++ b/test/deprecated/legacy_test/test_bfgs_deprecated.py @@ -96,15 +96,15 @@ def func(x): ) def test_inf_minima(self): - extream_point = np.array([-1, 2]).astype('float32') + extreme_point = np.array([-1, 2]).astype('float32') def func(x): # df = 3(x - 1.01)(x - 0.99) # f = x^3 - 3x^2 + 3*1.01*0.99x return ( x * x * x / 3.0 - - (extream_point[0] + extream_point[1]) * x * x / 2 - + extream_point[0] * extream_point[1] * x + - (extreme_point[0] + extreme_point[1]) * x * x / 2 + + extreme_point[0] * extreme_point[1] * x ) x0 = np.array([-1.7]).astype('float32') diff --git a/test/deprecated/legacy_test/test_lbfgs_deprecated.py b/test/deprecated/legacy_test/test_lbfgs_deprecated.py index a13aeadb084664..2c3594f9d19a92 100644 --- a/test/deprecated/legacy_test/test_lbfgs_deprecated.py +++ b/test/deprecated/legacy_test/test_lbfgs_deprecated.py @@ -92,15 +92,15 @@ def func(x): np.testing.assert_allclose(minimum, results[2].numpy(), rtol=1e-05) def test_inf_minima(self): - extream_point = np.array([-1, 2]).astype('float32') + extreme_point = np.array([-1, 2]).astype('float32') def func(x): # df = 3(x - 1.01)(x - 0.99) # f = x^3 - 3x^2 + 3*1.01*0.99x return ( x * x * x / 3.0 - - (extream_point[0] + extream_point[1]) * x * x / 2 - + extream_point[0] * extream_point[1] * x + - (extreme_point[0] + extreme_point[1]) * x * x / 2 + + extreme_point[0] * extreme_point[1] * x ) x0 = np.array([-1.7]).astype('float32') diff --git a/test/legacy_test/test_lbfgs_class.py b/test/legacy_test/test_lbfgs_class.py index 17b2e88587cc07..4ad7825237cfcd 100644 --- a/test/legacy_test/test_lbfgs_class.py +++ b/test/legacy_test/test_lbfgs_class.py @@ -103,18 +103,18 @@ def outputs2(x): targets = [outputs1(input), outputs2(input)] input = paddle.to_tensor(input) - def func1(extream_point, x): + def func1(extreme_point, x): return ( x * x * x - 3 * x * x - + 3 * extream_point[0] * extream_point[1] * x + + 3 * extreme_point[0] * extreme_point[1] * x ) - def func2(extream_point, x): - return pow(x, extream_point[0]) + 5 * pow(x, extream_point[1]) + def func2(extreme_point, x): + return pow(x, extreme_point[0]) + 5 * pow(x, extreme_point[1]) - extream_point = np.array([-2.34, 1.45]).astype('float32') - net1 = Net(extream_point, func1) + extreme_point = np.array([-2.34, 1.45]).astype('float32') + net1 = Net(extreme_point, func1) # converge of old_sk.pop() opt1 = incubate_lbfgs.LBFGS( learning_rate=1, @@ -127,7 +127,7 @@ def func2(extream_point, x): parameters=net1.parameters(), ) - net2 = Net(extream_point, func2) + net2 = Net(extreme_point, func2) # converge of line_search = None opt2 = incubate_lbfgs.LBFGS( learning_rate=1, @@ -153,8 +153,8 @@ def func2(extream_point, x): def test_error_incubate(self): # test parameter is not Paddle Tensor def error_func1(): - extream_point = np.array([-1, 2]).astype('float32') - extream_point = paddle.to_tensor(extream_point) + extreme_point = np.array([-1, 2]).astype('float32') + extreme_point = paddle.to_tensor(extreme_point) return incubate_lbfgs.LBFGS( learning_rate=1, max_iter=10, @@ -163,7 +163,7 @@ def error_func1(): tolerance_change=1e-09, history_size=3, line_search_fn='strong_wolfe', - parameters=extream_point, + parameters=extreme_point, ) self.assertRaises(TypeError, error_func1) @@ -179,11 +179,11 @@ def outputs2(x): targets = [outputs2(input)] input = paddle.to_tensor(input) - def func2(extream_point, x): - return pow(x, extream_point[0]) + 5 * pow(x, extream_point[1]) + def func2(extreme_point, x): + return pow(x, extreme_point[0]) + 5 * pow(x, extreme_point[1]) - extream_point = np.array([-2.34, 1.45]).astype('float32') - net2 = Net(extream_point, func2) + extreme_point = np.array([-2.34, 1.45]).astype('float32') + net2 = Net(extreme_point, func2) # converge of line_search = None opt2 = incubate_lbfgs.LBFGS( learning_rate=1, @@ -283,13 +283,13 @@ def func3(x, alpha, d): def test_error3_incubate(self): # test parameter shape size <= 0 def error_func3(): - extream_point = np.array([-1, 2]).astype('float32') - extream_point = paddle.to_tensor(extream_point) + extreme_point = np.array([-1, 2]).astype('float32') + extreme_point = paddle.to_tensor(extreme_point) def func(w, x): return w * x - net = Net(extream_point, func) + net = Net(extreme_point, func) net.w = paddle.create_parameter( shape=[-1, 2], dtype=net.w.dtype, @@ -353,18 +353,18 @@ def outputs2(x): targets = [outputs1(input), outputs2(input)] input = paddle.to_tensor(input) - def func1(extream_point, x): + def func1(extreme_point, x): return ( x * x * x - 3 * x * x - + 3 * extream_point[0] * extream_point[1] * x + + 3 * extreme_point[0] * extreme_point[1] * x ) - def func2(extream_point, x): - return pow(x, extream_point[0]) + 5 * pow(x, extream_point[1]) + def func2(extreme_point, x): + return pow(x, extreme_point[0]) + 5 * pow(x, extreme_point[1]) - extream_point = np.array([-2.34, 1.45]).astype('float32') - net1 = Net(extream_point, func1) + extreme_point = np.array([-2.34, 1.45]).astype('float32') + net1 = Net(extreme_point, func1) # converge of old_sk.pop() opt1 = lbfgs.LBFGS( learning_rate=1, @@ -377,7 +377,7 @@ def func2(extream_point, x): parameters=net1.parameters(), ) - net2 = Net(extream_point, func2) + net2 = Net(extreme_point, func2) # converge of line_search = None opt2 = lbfgs.LBFGS( learning_rate=1, @@ -403,8 +403,8 @@ def func2(extream_point, x): def test_error(self): # test parameter is not Paddle Tensor def error_func1(): - extream_point = np.array([-1, 2]).astype('float32') - extream_point = paddle.to_tensor(extream_point) + extreme_point = np.array([-1, 2]).astype('float32') + extreme_point = paddle.to_tensor(extreme_point) return lbfgs.LBFGS( learning_rate=1, max_iter=10, @@ -413,7 +413,7 @@ def error_func1(): tolerance_change=1e-09, history_size=3, line_search_fn='strong_wolfe', - parameters=extream_point, + parameters=extreme_point, ) self.assertRaises(TypeError, error_func1) @@ -429,11 +429,11 @@ def outputs2(x): targets = [outputs2(input)] input = paddle.to_tensor(input) - def func2(extream_point, x): - return pow(x, extream_point[0]) + 5 * pow(x, extream_point[1]) + def func2(extreme_point, x): + return pow(x, extreme_point[0]) + 5 * pow(x, extreme_point[1]) - extream_point = np.array([-2.34, 1.45]).astype('float32') - net2 = Net(extream_point, func2) + extreme_point = np.array([-2.34, 1.45]).astype('float32') + net2 = Net(extreme_point, func2) # converge of line_search = None opt2 = lbfgs.LBFGS( learning_rate=1, @@ -543,13 +543,13 @@ def func3(x, alpha, d): def test_error3(self): # test parameter shape size <= 0 def error_func3(): - extream_point = np.array([-1, 2]).astype('float32') - extream_point = paddle.to_tensor(extream_point) + extreme_point = np.array([-1, 2]).astype('float32') + extreme_point = paddle.to_tensor(extreme_point) def func(w, x): return w * x - net = Net(extream_point, func) + net = Net(extreme_point, func) net.w = paddle.create_parameter( shape=[-1, 2], dtype=net.w.dtype, @@ -576,12 +576,12 @@ def error_func4(): targets = paddle.to_tensor([inputs * 2]) inputs = paddle.to_tensor(inputs) - extream_point = np.array([-1, 1]).astype('float32') + extreme_point = np.array([-1, 1]).astype('float32') - def func(extream_point, x): - return x * extream_point[0] + 5 * x * extream_point[1] + def func(extreme_point, x): + return x * extreme_point[0] + 5 * x * extreme_point[1] - net = Net(extream_point, func) + net = Net(extreme_point, func) opt = lbfgs.LBFGS( learning_rate=1, max_iter=10,