From d8a9ba56ef8bece64a48de43b5b2bca48267c197 Mon Sep 17 00:00:00 2001 From: lijianshe02 <48898730+lijianshe02@users.noreply.github.com> Date: Mon, 18 Jan 2021 10:39:02 +0800 Subject: [PATCH] fix random seed in nll_loss unittest test=develop (#30468) --- .../fluid/tests/unittests/test_nll_loss.py | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/python/paddle/fluid/tests/unittests/test_nll_loss.py b/python/paddle/fluid/tests/unittests/test_nll_loss.py index ee7e3a6528..a87d9052bd 100644 --- a/python/paddle/fluid/tests/unittests/test_nll_loss.py +++ b/python/paddle/fluid/tests/unittests/test_nll_loss.py @@ -74,6 +74,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_mean(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) prog = fluid.Program() startup_prog = fluid.Program() @@ -108,6 +109,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_sum(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) prog = fluid.Program() startup_prog = fluid.Program() @@ -142,6 +144,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_with_weight_mean(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) weight_np = np.random.random(size=(10, )).astype(np.float64) prog = fluid.Program() @@ -181,6 +184,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_with_weight_sum(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) weight_np = np.random.random(size=(10, )).astype(np.float64) prog = fluid.Program() @@ -221,6 +225,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_with_weight_mean_cpu(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) weight_np = np.random.random(size=(10, )).astype(np.float64) prog = fluid.Program() @@ -258,6 +263,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_1D_with_weight_no_reduce_cpu(self): np.random.seed(200) input_np = np.random.random(size=(10, 10)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 10, size=(10, )).astype(np.int64) weight_np = np.random.random(size=(10, )).astype(np.float64) prog = fluid.Program() @@ -296,6 +302,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_2D_mean(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5)).astype(np.int64) prog = fluid.Program() startup_prog = fluid.Program() @@ -332,6 +339,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_2D_sum(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5)).astype(np.int64) prog = fluid.Program() startup_prog = fluid.Program() @@ -368,6 +376,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_2D_with_weight_mean(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -410,6 +419,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_2D_with_weight_mean_cpu(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -450,6 +460,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_2D_with_weight_sum(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -492,6 +503,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_in_dims_not_2or4_mean(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5, 5)).astype(np.int64) prog = fluid.Program() startup_prog = fluid.Program() @@ -533,6 +545,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_in_dims_not_2or4_with_weight_mean(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -580,6 +593,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_in_dims_not_2or4_with_weight_sum(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -630,6 +644,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_in_dims_not_2or4_with_weight_no_reduce(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -681,6 +696,7 @@ class TestNLLLoss(unittest.TestCase): def test_NLLLoss_in_dims_not_2or4_with_weight_no_reduce_cpu(self): np.random.seed(200) input_np = np.random.random(size=(5, 3, 5, 5, 5)).astype(np.float64) + np.random.seed(200) label_np = np.random.randint(0, 3, size=(5, 5, 5, 5)).astype(np.int64) weight_np = np.random.random(size=(3, )).astype(np.float64) prog = fluid.Program() @@ -736,11 +752,13 @@ class TestNLLLossOp1DWithReduce(OpTest): np.random.seed(200) input_np = np.random.uniform(0.1, 0.8, self.input_shape).astype("float64") + np.random.seed(200) label_np = np.random.randint(0, self.input_shape[1], self.label_shape).astype("int64") output_np, total_weight_np = nll_loss_1d(input_np, label_np) self.inputs = {'X': input_np, 'Label': label_np} if self.with_weight: + np.random.seed(200) weight_np = np.random.uniform(0.1, 0.8, self.input_shape[1]).astype("float64") output_np, total_weight_np = nll_loss_1d( @@ -778,12 +796,14 @@ class TestNLLLossOp1DNoReduce(OpTest): np.random.seed(200) input_np = np.random.uniform(0.1, 0.8, self.input_shape).astype("float64") + np.random.seed(200) label_np = np.random.randint(0, self.input_shape[1], self.label_shape).astype("int64") output_np = nll_loss_1d(input_np, label_np, reduction='none') total_weight_np = np.array([0]).astype('float64') self.inputs = {'X': input_np, 'Label': label_np} if self.with_weight: + np.random.seed(200) weight_np = np.random.uniform(0.1, 0.8, self.input_shape[1]).astype("float64") output_np, total_weight_np = nll_loss_1d( @@ -865,12 +885,14 @@ class TestNLLLossOp2DNoReduce(OpTest): np.random.seed(200) input_np = np.random.uniform(0.1, 0.8, self.input_shape).astype("float64") + np.random.seed(200) label_np = np.random.randint(0, self.input_shape[1], self.label_shape).astype("int64") output_np = nll_loss_2d(input_np, label_np, reduction='none') total_weight_np = np.array([0]).astype('float64') self.inputs = {'X': input_np, 'Label': label_np} if self.with_weight: + np.random.seed(200) weight_np = np.random.uniform(0.1, 0.8, self.input_shape[1]).astype("float64") output_np, total_weight_np = nll_loss_2d( -- GitLab