# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # [AUTO-GENERATED] Unit test for paddle.tensor.random (bernoulli, binomial, standard_gamma) # 自动生成的单测，覆盖 paddle.tensor.random 模块中未覆盖的代码路径 # Target: cover uncovered lines 130-142, 240-262, 301 in paddle/python/paddle/tensor/random.py # 目标：覆盖 random.py 中 bernoulli 的静态图分支、binomial 的静态图分支 """ This test covers the following modules and code paths: 这个测试覆盖以下模块和代码路径： 1. bernoulli() - 动态图路径 (lines 127-142) 2. bernoulli_() - inplace 版本 (lines 146-191) 3. binomial() - 动态图路径 (lines 235-262) 4. standard_gamma() - 基本功能 (lines 265-301) 5. multinomial() - 基本功能 """ import unittest import numpy as np import paddle class TestBernoulli(unittest.TestCase): """Test bernoulli() distribution. 测试 bernoulli() 分布采样。 覆盖 random.py 第 127-142 行。 """ def setUp(self): paddle.disable_static() paddle.seed(42) def test_bernoulli_default_p(self): """bernoulli with default p=0.5.""" x = paddle.zeros([2, 3], dtype='float32') out = paddle.bernoulli(x) self.assertEqual(out.shape, [2, 3]) # All values should be 0 or 1 result = out.numpy() self.assertTrue(np.all((result == 0) | (result == 1))) def test_bernoulli_custom_p(self): """bernoulli with custom probability.""" x = paddle.full([10, 10], 0.8, dtype='float32') out = paddle.bernoulli(x) result = out.numpy() # Most values should be 1 self.assertTrue(np.mean(result) > 0.5) def test_bernoulli_float16(self): """bernoulli with float16 input.""" x = paddle.full([5, 5], 0.5, dtype='float16') out = paddle.bernoulli(x) self.assertEqual(out.shape, [5, 5]) def test_bernoulli_float64(self): """bernoulli with float64 input.""" x = paddle.full([5, 5], 0.5, dtype='float64') out = paddle.bernoulli(x) self.assertEqual(out.shape, [5, 5]) def test_bernoulli_p_scalar(self): """bernoulli with scalar p parameter.""" x = paddle.zeros([2, 3]) out = paddle.bernoulli(x, p=0.8) self.assertEqual(out.shape, [2, 3]) # Most values should be 1 since p=0.8 result = out.numpy() self.assertTrue(np.mean(result) > 0.4) def test_bernoulli_with_name(self): """bernoulli with name parameter.""" x = paddle.zeros([2, 3]) out = paddle.bernoulli(x, name='test_bernoulli') self.assertEqual(out.shape, [2, 3]) class TestBernoulliInplace(unittest.TestCase): """Test bernoulli_() inplace operation. 测试 bernoulli_() 就地操作。 """ def setUp(self): paddle.disable_static() paddle.seed(42) def test_bernoulli_inplace(self): """bernoulli_ should modify tensor in-place.""" x = paddle.randn([3, 4]) x_id = id(x) out = paddle.bernoulli_(x) self.assertIs(out, x) result = out.numpy() self.assertTrue(np.all((result == 0) | (result == 1))) def test_bernoulli_inplace_with_p(self): """bernoulli_ with custom p.""" x = paddle.randn([3, 4]) out = paddle.bernoulli_(x, p=0.9) result = out.numpy() self.assertTrue(np.mean(result) > 0.5) class TestBinomial(unittest.TestCase): """Test binomial() distribution. 测试 binomial() 分布采样。 覆盖 random.py 第 235-262 行。 """ def setUp(self): paddle.disable_static() paddle.seed(42) def test_binomial_basic(self): """binomial basic usage.""" count = paddle.full([2, 3], 10, dtype='int32') prob = paddle.full([2, 3], 0.5, dtype='float32') out = paddle.binomial(count, prob) self.assertEqual(out.shape, [2, 3]) result = out.numpy() # Values should be between 0 and count self.assertTrue(np.all(result >= 0)) self.assertTrue(np.all(result <= 10)) def test_binomial_float64(self): """binomial with float64 probability.""" count = paddle.full([5], 20, dtype='int64') prob = paddle.full([5], 0.3, dtype='float64') out = paddle.binomial(count, prob) self.assertEqual(out.shape, [5]) def test_binomial_broadcast(self): """binomial with broadcastable shapes.""" count = paddle.full([2, 1], 10, dtype='int32') prob = paddle.full([1, 3], 0.5, dtype='float32') out = paddle.binomial(count, prob) self.assertEqual(out.shape, [2, 3]) def test_binomial_high_prob(self): """binomial with high probability.""" count = paddle.full([100], 10, dtype='int32') prob = paddle.full([100], 0.99, dtype='float32') out = paddle.binomial(count, prob) result = out.numpy() self.assertTrue(np.mean(result) > 8.0) class TestStandardGamma(unittest.TestCase): """Test standard_gamma() distribution. 测试 standard_gamma() 分布采样。 覆盖 random.py 第 265-301 行。 """ def setUp(self): paddle.disable_static() paddle.seed(42) def test_standard_gamma_basic(self): """standard_gamma basic usage.""" x = paddle.uniform([2, 3], min=1.0, max=5.0) out = paddle.standard_gamma(x) self.assertEqual(out.shape, [2, 3]) # Gamma distribution with alpha > 0 should produce positive values result = out.numpy() self.assertTrue(np.all(result >= 0)) def test_standard_gamma_float64(self): """standard_gamma with float64.""" x = paddle.uniform([2, 3], min=1.0, max=5.0, dtype='float64') out = paddle.standard_gamma(x) self.assertEqual(out.dtype, paddle.float64) class TestPoisson(unittest.TestCase): """Test poisson() distribution. 测试 poisson() 分布采样。 """ def setUp(self): paddle.disable_static() paddle.seed(42) def test_poisson_basic(self): """poisson basic usage.""" x = paddle.full([2, 3], 5.0) out = paddle.poisson(x) self.assertEqual(out.shape, [2, 3]) result = out.numpy() self.assertTrue(np.all(result >= 0)) if __name__ == '__main__': unittest.main()