From b71833ea4a98a1f9cbee6b769c25b72072f20539 Mon Sep 17 00:00:00 2001
From: Zhou Wei <1183042833@qq.com>
Date: Mon, 1 Aug 2022 17:36:52 +0800
Subject: [PATCH] [UT]fix test_poisson op random fail (#44763)
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修复poisson op单测随机挂

原因：由于随机OP的无法直接验证数值正确性，该单测随机采样100万个样本，统计落到直方图各区间的数量，计算出粗略的概率密度函数，与标准概率密度函数对比，这种测试方式会有一定误差。
当采样数量越小，误差越大，因此该PR增大采样样本数量（100万->200万），误差进一步减小在rtol范围内。
---
 .../fluid/tests/unittests/test_poisson_op.py  | 20 +++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/python/paddle/fluid/tests/unittests/test_poisson_op.py b/python/paddle/fluid/tests/unittests/test_poisson_op.py
index 812770fac3a..03259e8d5a1 100644
--- a/python/paddle/fluid/tests/unittests/test_poisson_op.py
+++ b/python/paddle/fluid/tests/unittests/test_poisson_op.py
@@ -39,13 +39,14 @@ def output_hist(out, lam, a, b):
 
 
 class TestPoissonOp1(OpTest):
+
     def setUp(self):
         self.op_type = "poisson"
         self.config()
 
         self.attrs = {}
-        self.inputs = {'X': np.full([1024, 1024], self.lam, dtype=self.dtype)}
-        self.outputs = {'Out': np.ones([1024, 1024], dtype=self.dtype)}
+        self.inputs = {'X': np.full([2048, 1024], self.lam, dtype=self.dtype)}
+        self.outputs = {'Out': np.ones([2048, 1024], dtype=self.dtype)}
 
     def config(self):
         self.lam = 10
@@ -55,10 +56,8 @@ class TestPoissonOp1(OpTest):
 
     def verify_output(self, outs):
         hist, prob = output_hist(np.array(outs[0]), self.lam, self.a, self.b)
-        self.assertTrue(
-            np.allclose(
-                hist, prob, rtol=0.01),
-            "actual: {}, expected: {}".format(hist, prob))
+        self.assertTrue(np.allclose(hist, prob, rtol=0.01),
+                        "actual: {}, expected: {}".format(hist, prob))
 
     def test_check_output(self):
         self.check_output_customized(self.verify_output)
@@ -67,22 +66,23 @@ class TestPoissonOp1(OpTest):
         self.check_grad(
             ['X'],
             'Out',
-            user_defined_grads=[np.zeros(
-                [1024, 1024], dtype=self.dtype)],
+            user_defined_grads=[np.zeros([2048, 1024], dtype=self.dtype)],
             user_defined_grad_outputs=[
-                np.random.rand(1024, 1024).astype(self.dtype)
+                np.random.rand(2048, 1024).astype(self.dtype)
             ])
 
 
 class TestPoissonOp2(TestPoissonOp1):
+
     def config(self):
         self.lam = 5
         self.a = 1
-        self.b = 9
+        self.b = 8
         self.dtype = "float32"
 
 
 class TestPoissonAPI(unittest.TestCase):
+
     def test_static(self):
         with paddle.static.program_guard(paddle.static.Program(),
                                          paddle.static.Program()):
-- 
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