From c8d32c8c1075c177164de57a9bdc894e5eb7e1b8 Mon Sep 17 00:00:00 2001 From: LutaoChu <30695251+LutaoChu@users.noreply.github.com> Date: Mon, 19 Oct 2020 17:19:24 +0800 Subject: [PATCH] Fix diag OP bug on Windows Python3.8 MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Fix diag OP bug on Windows Python3.8 ，remove the std::min --- paddle/fluid/operators/diag_v2_op.cc | 24 +- .../paddle/fluid/tests/unittests/test_diag.py | 220 +-------------- .../fluid/tests/unittests/test_diag_v2.py | 260 ++++++++++++++++++ 3 files changed, 280 insertions(+), 224 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/test_diag_v2.py diff --git a/paddle/fluid/operators/diag_v2_op.cc b/paddle/fluid/operators/diag_v2_op.cc index 67dc2843345..ae78517182a 100644 --- a/paddle/fluid/operators/diag_v2_op.cc +++ b/paddle/fluid/operators/diag_v2_op.cc @@ -32,16 +32,28 @@ class DiagV2Op : public framework::OperatorWithKernel { auto offset = ctx->Attrs().Get("offset"); if (x_dims.size() == 1UL) { - int64_t size = x_dims[0] + std::abs(offset); - ctx->SetOutputDim("Out", {size, size}); + int64_t size_ = x_dims[0] + std::abs(offset); + ctx->SetOutputDim("Out", {size_, size_}); } else if (x_dims.size() == 2UL) { - int64_t size; + int64_t size_ = 0; if (offset >= 0) { - size = std::min(x_dims[0], x_dims[1] - offset); + // Note(LutaoChu): Do not use std::min here, otherwise the calculation + // of `size_` will have unexpected result on Windows Python3.8 + if (x_dims[0] < x_dims[1] - offset) { + size_ = x_dims[0]; + } else { + size_ = x_dims[1] - offset; + } } else { - size = std::min(x_dims[0] + offset, x_dims[1]); + // Note(LutaoChu): Do not use std::min here, otherwise the calculation + // of `size_` will have unexpected result on Windows Python3.8 + if (x_dims[0] + offset < x_dims[1]) { + size_ = x_dims[0] + offset; + } else { + size_ = x_dims[1]; + } } - ctx->SetOutputDim("Out", {size}); + ctx->SetOutputDim("Out", {size_}); } else { PADDLE_THROW(platform::errors::InvalidArgument( "The input tensor X's dimensions of DiagV2Op should be either 1 or " diff --git a/python/paddle/fluid/tests/unittests/test_diag.py b/python/paddle/fluid/tests/unittests/test_diag.py index 94a51301d51..29f5a90726d 100644 --- a/python/paddle/fluid/tests/unittests/test_diag.py +++ b/python/paddle/fluid/tests/unittests/test_diag.py @@ -23,224 +23,6 @@ from paddle.fluid import core from paddle.fluid import Program, program_guard -class TestDiagV2Op(OpTest): - def setUp(self): - self.op_type = "diag_v2" - self.x = np.random.rand(10, 10) - self.offset = 0 - self.padding_value = 0.0 - self.out = np.diag(self.x, self.offset) - - self.init_config() - self.inputs = {'X': self.x} - self.attrs = { - 'offset': self.offset, - 'padding_value': self.padding_value - } - self.outputs = {'Out': self.out} - - def test_check_output(self): - self.check_output() - - def init_config(self): - pass - - -class TestDiagV2OpCase1(TestDiagV2Op): - def init_config(self): - self.offset = 1 - self.out = np.diag(self.x, self.offset) - - -class TestDiagV2OpCase2(TestDiagV2Op): - def init_config(self): - self.offset = -1 - self.out = np.diag(self.x, self.offset) - - -class TestDiagV2OpCase3(TestDiagV2Op): - def init_config(self): - self.x = np.random.randint(-10, 10, size=(10, 10)) - self.out = np.diag(self.x, self.offset) - - -class TestDiagV2OpCase4(TestDiagV2Op): - def init_config(self): - self.x = np.random.rand(100) - self.padding_value = 8 - n = self.x.size - self.out = self.padding_value * np.ones((n, n)) + np.diag( - self.x, self.offset) - np.diag(self.padding_value * np.ones(n)) - - -class TestDiagV2Error(unittest.TestCase): - def test_errors(self): - with program_guard(Program(), Program()): - - def test_diag_v2_type(): - x = [1, 2, 3] - output = paddle.diag(x) - - self.assertRaises(TypeError, test_diag_v2_type) - - x = paddle.static.data('data', [3, 3]) - self.assertRaises(TypeError, paddle.diag, x, offset=2.5) - - self.assertRaises(TypeError, paddle.diag, x, padding_value=[9]) - - x = paddle.static.data('data2', [3, 3, 3]) - self.assertRaises(ValueError, paddle.diag, x) - - -class TestDiagV2API(unittest.TestCase): - def setUp(self): - self.input_np = np.random.random(size=(10, 10)).astype(np.float32) - self.expected0 = np.diag(self.input_np) - self.expected1 = np.diag(self.input_np, k=1) - self.expected2 = np.diag(self.input_np, k=-1) - - self.input_np2 = np.random.rand(100) - self.offset = 0 - self.padding_value = 8 - n = self.input_np2.size - self.expected3 = self.padding_value * np.ones( - (n, n)) + np.diag(self.input_np2, self.offset) - np.diag( - self.padding_value * np.ones(n)) - - self.input_np3 = np.random.randint(-10, 10, size=(100)).astype(np.int64) - self.padding_value = 8.0 - n = self.input_np3.size - self.expected4 = self.padding_value * np.ones( - (n, n)) + np.diag(self.input_np3, self.offset) - np.diag( - self.padding_value * np.ones(n)) - - self.padding_value = -8 - self.expected5 = self.padding_value * np.ones( - (n, n)) + np.diag(self.input_np3, self.offset) - np.diag( - self.padding_value * np.ones(n)) - - self.input_np4 = np.random.random(size=(2000, 2000)).astype(np.float32) - self.expected6 = np.diag(self.input_np4) - self.expected7 = np.diag(self.input_np4, k=1) - self.expected8 = np.diag(self.input_np4, k=-1) - - self.input_np5 = np.random.random(size=(2000)).astype(np.float32) - self.expected9 = np.diag(self.input_np5) - self.expected10 = np.diag(self.input_np5, k=1) - self.expected11 = np.diag(self.input_np5, k=-1) - - def run_imperative(self): - x = paddle.to_tensor(self.input_np) - y = paddle.diag(x) - self.assertTrue(np.allclose(y.numpy(), self.expected0)) - - y = paddle.diag(x, offset=1) - self.assertTrue(np.allclose(y.numpy(), self.expected1)) - - y = paddle.diag(x, offset=-1) - self.assertTrue(np.allclose(y.numpy(), self.expected2)) - - x = paddle.to_tensor(self.input_np2) - y = paddle.diag(x, padding_value=8) - self.assertTrue(np.allclose(y.numpy(), self.expected3)) - - x = paddle.to_tensor(self.input_np3) - y = paddle.diag(x, padding_value=8.0) - self.assertTrue(np.allclose(y.numpy(), self.expected4)) - - y = paddle.diag(x, padding_value=-8) - self.assertTrue(np.allclose(y.numpy(), self.expected5)) - - x = paddle.to_tensor(self.input_np4) - y = paddle.diag(x) - self.assertTrue(np.allclose(y.numpy(), self.expected6)) - - y = paddle.diag(x, offset=1) - self.assertTrue(np.allclose(y.numpy(), self.expected7)) - - y = paddle.diag(x, offset=-1) - self.assertTrue(np.allclose(y.numpy(), self.expected8)) - - x = paddle.to_tensor(self.input_np5) - y = paddle.diag(x) - self.assertTrue(np.allclose(y.numpy(), self.expected9)) - - y = paddle.diag(x, offset=1) - self.assertTrue(np.allclose(y.numpy(), self.expected10)) - - y = paddle.diag(x, offset=-1) - self.assertTrue(np.allclose(y.numpy(), self.expected11)) - - def run_static(self, use_gpu=False): - x = paddle.fluid.data(name='input', shape=[10, 10], dtype='float32') - x2 = paddle.fluid.data(name='input2', shape=[100], dtype='float64') - x3 = paddle.fluid.data(name='input3', shape=[100], dtype='int64') - x4 = paddle.fluid.data(name='input4', shape=[2000, 2000], dtype='float32') - x5 = paddle.fluid.data(name='input5', shape=[2000], dtype='float32') - result0 = paddle.diag(x) - result1 = paddle.diag(x, offset=1) - result2 = paddle.diag(x, offset=-1) - result3 = paddle.diag(x, name='aaa') - result4 = paddle.diag(x2, padding_value=8) - result5 = paddle.diag(x3, padding_value=8.0) - result6 = paddle.diag(x3, padding_value=-8) - result7 = paddle.diag(x4) - result8 = paddle.diag(x4, offset=1) - result9 = paddle.diag(x4, offset=-1) - result10 = paddle.diag(x5) - result11 = paddle.diag(x5, offset=1) - result12 = paddle.diag(x5, offset=-1) - - place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace() - exe = fluid.Executor(place) - exe.run(fluid.default_startup_program()) - res0, res1, res2, res4, res5, res6, res7, res8, res9, res10, res11, res12 = exe.run( - feed={ - "input": self.input_np, - "input2": self.input_np2, - 'input3': self.input_np3, - 'input4': self.input_np4, - 'input5': self.input_np5 - }, - fetch_list=[ - result0, result1, result2, result4, result5, result6, result7, - result8, result9, result10, result11, result12 - ]) - - self.assertTrue(np.allclose(res0, self.expected0)) - self.assertTrue(np.allclose(res1, self.expected1)) - self.assertTrue(np.allclose(res2, self.expected2)) - self.assertTrue('aaa' in result3.name) - self.assertTrue(np.allclose(res4, self.expected3)) - self.assertTrue(np.allclose(res5, self.expected4)) - self.assertTrue(np.allclose(res6, self.expected5)) - self.assertTrue(np.allclose(res7, self.expected6)) - self.assertTrue(np.allclose(res8, self.expected7)) - self.assertTrue(np.allclose(res9, self.expected8)) - self.assertTrue(np.allclose(res10, self.expected9)) - self.assertTrue(np.allclose(res11, self.expected10)) - self.assertTrue(np.allclose(res12, self.expected11)) - - def test_cpu(self): - paddle.disable_static(place=paddle.fluid.CPUPlace()) - self.run_imperative() - paddle.enable_static() - - with fluid.program_guard(fluid.Program()): - self.run_static() - - def test_gpu(self): - if not fluid.core.is_compiled_with_cuda(): - return - - paddle.disable_static(place=paddle.fluid.CUDAPlace(0)) - self.run_imperative() - paddle.enable_static() - - with fluid.program_guard(fluid.Program()): - self.run_static(use_gpu=True) - - class TestDiagOp(OpTest): def setUp(self): self.op_type = "diag" @@ -250,6 +32,7 @@ class TestDiagOp(OpTest): self.outputs = {'Out': np.diag(self.inputs['Diagonal'])} def test_check_output(self): + paddle.enable_static() self.check_output() def init_config(self): @@ -263,6 +46,7 @@ class TestDiagOpCase1(TestDiagOp): class TestDiagError(unittest.TestCase): def test_errors(self): + paddle.enable_static() with program_guard(Program(), Program()): def test_diag_type(): diff --git a/python/paddle/fluid/tests/unittests/test_diag_v2.py b/python/paddle/fluid/tests/unittests/test_diag_v2.py new file mode 100644 index 00000000000..c364fb0a193 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_diag_v2.py @@ -0,0 +1,260 @@ +# Copyright (c) 2019 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 numpy as np +from op_test import OpTest +import paddle +import paddle.fluid as fluid +from paddle.fluid import core +from paddle.fluid import Program, program_guard + + +class TestDiagV2Op(OpTest): + def setUp(self): + self.op_type = "diag_v2" + self.x = np.random.rand(10, 10) + self.offset = 0 + self.padding_value = 0.0 + self.out = np.diag(self.x, self.offset) + + self.init_config() + self.inputs = {'X': self.x} + self.attrs = { + 'offset': self.offset, + 'padding_value': self.padding_value + } + self.outputs = {'Out': self.out} + + def test_check_output(self): + paddle.enable_static() + self.check_output() + + def init_config(self): + pass + + +class TestDiagV2OpCase1(TestDiagV2Op): + def init_config(self): + self.offset = 1 + self.out = np.diag(self.x, self.offset) + + +class TestDiagV2OpCase2(TestDiagV2Op): + def init_config(self): + self.offset = -1 + self.out = np.diag(self.x, self.offset) + + +class TestDiagV2OpCase3(TestDiagV2Op): + def init_config(self): + self.x = np.random.randint(-10, 10, size=(10, 10)) + self.out = np.diag(self.x, self.offset) + + +class TestDiagV2OpCase4(TestDiagV2Op): + def init_config(self): + self.x = np.random.rand(100) + self.padding_value = 8 + n = self.x.size + self.out = self.padding_value * np.ones((n, n)) + np.diag( + self.x, self.offset) - np.diag(self.padding_value * np.ones(n)) + + +class TestDiagV2Error(unittest.TestCase): + def test_errors(self): + paddle.enable_static() + with program_guard(Program(), Program()): + + def test_diag_v2_type(): + x = [1, 2, 3] + output = paddle.diag(x) + + self.assertRaises(TypeError, test_diag_v2_type) + + x = paddle.static.data('data', [3, 3]) + self.assertRaises(TypeError, paddle.diag, x, offset=2.5) + + self.assertRaises(TypeError, paddle.diag, x, padding_value=[9]) + + x = paddle.static.data('data2', [3, 3, 3]) + self.assertRaises(ValueError, paddle.diag, x) + + +class TestDiagV2API(unittest.TestCase): + def setUp(self): + self.input_np = np.random.random(size=(10, 10)).astype(np.float32) + self.expected0 = np.diag(self.input_np) + self.expected1 = np.diag(self.input_np, k=1) + self.expected2 = np.diag(self.input_np, k=-1) + + self.input_np2 = np.random.rand(100) + self.offset = 0 + self.padding_value = 8 + n = self.input_np2.size + self.expected3 = self.padding_value * np.ones( + (n, n)) + np.diag(self.input_np2, self.offset) - np.diag( + self.padding_value * np.ones(n)) + + self.input_np3 = np.random.randint(-10, 10, size=(100)).astype(np.int64) + self.padding_value = 8.0 + n = self.input_np3.size + self.expected4 = self.padding_value * np.ones( + (n, n)) + np.diag(self.input_np3, self.offset) - np.diag( + self.padding_value * np.ones(n)) + + self.padding_value = -8 + self.expected5 = self.padding_value * np.ones( + (n, n)) + np.diag(self.input_np3, self.offset) - np.diag( + self.padding_value * np.ones(n)) + + self.input_np4 = np.random.random(size=(2000, 2000)).astype(np.float32) + self.expected6 = np.diag(self.input_np4) + self.expected7 = np.diag(self.input_np4, k=1) + self.expected8 = np.diag(self.input_np4, k=-1) + + self.input_np5 = np.random.random(size=(2000)).astype(np.float32) + self.expected9 = np.diag(self.input_np5) + self.expected10 = np.diag(self.input_np5, k=1) + self.expected11 = np.diag(self.input_np5, k=-1) + + self.input_np6 = np.random.random(size=(2000, 1500)).astype(np.float32) + self.expected12 = np.diag(self.input_np6, k=-1) + + def run_imperative(self): + x = paddle.to_tensor(self.input_np) + y = paddle.diag(x) + self.assertTrue(np.allclose(y.numpy(), self.expected0)) + + y = paddle.diag(x, offset=1) + self.assertTrue(np.allclose(y.numpy(), self.expected1)) + + y = paddle.diag(x, offset=-1) + self.assertTrue(np.allclose(y.numpy(), self.expected2)) + + x = paddle.to_tensor(self.input_np2) + y = paddle.diag(x, padding_value=8) + self.assertTrue(np.allclose(y.numpy(), self.expected3)) + + x = paddle.to_tensor(self.input_np3) + y = paddle.diag(x, padding_value=8.0) + self.assertTrue(np.allclose(y.numpy(), self.expected4)) + + y = paddle.diag(x, padding_value=-8) + self.assertTrue(np.allclose(y.numpy(), self.expected5)) + + x = paddle.to_tensor(self.input_np4) + y = paddle.diag(x) + self.assertTrue(np.allclose(y.numpy(), self.expected6)) + + y = paddle.diag(x, offset=1) + self.assertTrue(np.allclose(y.numpy(), self.expected7)) + + y = paddle.diag(x, offset=-1) + self.assertTrue(np.allclose(y.numpy(), self.expected8)) + + x = paddle.to_tensor(self.input_np5) + y = paddle.diag(x) + self.assertTrue(np.allclose(y.numpy(), self.expected9)) + + y = paddle.diag(x, offset=1) + self.assertTrue(np.allclose(y.numpy(), self.expected10)) + + y = paddle.diag(x, offset=-1) + self.assertTrue(np.allclose(y.numpy(), self.expected11)) + + x = paddle.to_tensor(self.input_np6) + y = paddle.diag(x, offset=-1) + self.assertTrue(np.allclose(y.numpy(), self.expected12)) + + def run_static(self, use_gpu=False): + x = paddle.static.data(name='input', shape=[10, 10], dtype='float32') + x2 = paddle.static.data(name='input2', shape=[100], dtype='float64') + x3 = paddle.static.data(name='input3', shape=[100], dtype='int64') + x4 = paddle.static.data( + name='input4', shape=[2000, 2000], dtype='float32') + x5 = paddle.static.data(name='input5', shape=[2000], dtype='float32') + x6 = paddle.static.data( + name='input6', shape=[2000, 1500], dtype='float32') + result0 = paddle.diag(x) + result1 = paddle.diag(x, offset=1) + result2 = paddle.diag(x, offset=-1) + result3 = paddle.diag(x, name='aaa') + result4 = paddle.diag(x2, padding_value=8) + result5 = paddle.diag(x3, padding_value=8.0) + result6 = paddle.diag(x3, padding_value=-8) + result7 = paddle.diag(x4) + result8 = paddle.diag(x4, offset=1) + result9 = paddle.diag(x4, offset=-1) + result10 = paddle.diag(x5) + result11 = paddle.diag(x5, offset=1) + result12 = paddle.diag(x5, offset=-1) + result13 = paddle.diag(x6, offset=-1) + + place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace() + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + res0, res1, res2, res4, res5, res6, res7, res8, res9, res10, res11, res12, res13 = exe.run( + feed={ + "input": self.input_np, + "input2": self.input_np2, + 'input3': self.input_np3, + 'input4': self.input_np4, + 'input5': self.input_np5, + 'input6': self.input_np6 + }, + fetch_list=[ + result0, result1, result2, result4, result5, result6, result7, + result8, result9, result10, result11, result12, result13 + ]) + + self.assertTrue(np.allclose(res0, self.expected0)) + self.assertTrue(np.allclose(res1, self.expected1)) + self.assertTrue(np.allclose(res2, self.expected2)) + self.assertTrue('aaa' in result3.name) + self.assertTrue(np.allclose(res4, self.expected3)) + self.assertTrue(np.allclose(res5, self.expected4)) + self.assertTrue(np.allclose(res6, self.expected5)) + self.assertTrue(np.allclose(res7, self.expected6)) + self.assertTrue(np.allclose(res8, self.expected7)) + self.assertTrue(np.allclose(res9, self.expected8)) + self.assertTrue(np.allclose(res10, self.expected9)) + self.assertTrue(np.allclose(res11, self.expected10)) + self.assertTrue(np.allclose(res12, self.expected11)) + self.assertTrue(np.allclose(res13, self.expected12)) + + def test_cpu(self): + paddle.disable_static(place=paddle.fluid.CPUPlace()) + self.run_imperative() + paddle.enable_static() + + with fluid.program_guard(fluid.Program()): + self.run_static() + + def test_gpu(self): + if not fluid.core.is_compiled_with_cuda(): + return + + paddle.disable_static(place=paddle.fluid.CUDAPlace(0)) + self.run_imperative() + paddle.enable_static() + + with fluid.program_guard(fluid.Program()): + self.run_static(use_gpu=True) + + +if __name__ == "__main__": + unittest.main() -- GitLab