# Copyright (c) 2018 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. from __future__ import print_function import unittest import paddle from op_test import OpTest import numpy as np def output_hist(out): hist, _ = np.histogram(out, bins=2) hist = hist.astype("float32") hist /= float(out.size) prob = 0.5 * np.ones((2)) return hist, prob class TestBernoulliOp(OpTest): def setUp(self): self.op_type = "bernoulli" self.inputs = {"X": np.random.uniform(size=(1000, 784))} self.attrs = {} self.outputs = {"Out": np.zeros((1000, 784)).astype("float32")} def test_check_output(self): self.check_output_customized(self.verify_output) def verify_output(self, outs): hist, prob = output_hist(np.array(outs[0])) self.assertTrue( np.allclose( hist, prob, rtol=0, atol=0.01), "hist: " + str(hist)) class TestBernoulliApi(unittest.TestCase): def test_dygraph(self): paddle.disable_static() x = paddle.rand([1024, 1024]) out = paddle.bernoulli(x) paddle.enable_static() hist, prob = output_hist(out.numpy()) self.assertTrue( np.allclose( hist, prob, rtol=0, atol=0.01), "hist: " + str(hist)) def test_static(self): x = paddle.rand([1024, 1024]) out = paddle.bernoulli(x) exe = paddle.static.Executor(paddle.CPUPlace()) out = exe.run(paddle.static.default_main_program(), fetch_list=[out.name]) hist, prob = output_hist(out[0]) self.assertTrue( np.allclose( hist, prob, rtol=0, atol=0.01), "hist: " + str(hist)) if __name__ == "__main__": unittest.main()