321 строка
14 KiB
C++
321 строка
14 KiB
C++
//
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// Copyright (c) Microsoft. All rights reserved.
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// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
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//
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// Tests for sparse and dense matrix interaction should go here
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//
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#include "stdafx.h"
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#include <random>
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#include "../../../Source/Math/Matrix.h"
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using namespace Microsoft::MSR::CNTK;
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namespace Microsoft { namespace MSR { namespace CNTK { namespace Test {
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// original dimensions: 4096, 2048, 128
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// some test fail with large dimensions (e.g. MatrixSparseElementWisePower)
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// reducing to:
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const size_t dim1 = 256;
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const size_t dim2 = 2048;
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const size_t dim3 = 128;
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BOOST_AUTO_TEST_SUITE(GPUMatrixSuite)
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BOOST_FIXTURE_TEST_CASE(MatrixChangeModesBetweenDenseAndSparse, RandomSeedFixture)
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{
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// This test should fail if you don't have CUDA GPU
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Matrix<float> mA(c_deviceIdZero);
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mA.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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float n0 = mA.MatrixNorm0();
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BOOST_CHECK_EQUAL(MatrixType::DENSE, mA.GetMatrixType());
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mA.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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BOOST_CHECK_EQUAL(MatrixType::SPARSE, mA.GetMatrixType());
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float n1 = mA.MatrixNorm0();
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BOOST_CHECK_EQUAL(n0, n1);
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mA.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, false);
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BOOST_CHECK_EQUAL(MatrixType::DENSE, mA.GetMatrixType());
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}
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BOOST_FIXTURE_TEST_CASE(MatrixSparseTimesDense, RandomSeedFixture)
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{
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// DENSE
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -300.0f, 0.1f, IncrementCounter()), 0);
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// MATRIX mAsparse becomes sparse
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Matrix<float> mAsparse(mAdense.DeepClone());
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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// DENSE
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Matrix<float> mB = Matrix<float>::RandomGaussian(dim2, dim3, c_deviceIdZero, 1.0f, 4.0f, IncrementCounter());
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Matrix<float> mC = Matrix<float>::RandomGaussian(dim1, dim3, c_deviceIdZero, 1.0f, 2.0f, IncrementCounter());
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Matrix<float> mD(mC.DeepClone());
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float alpha = 0.3f;
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float beta = 2.0f;
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bool transposeA = false, transposeB = false;
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// DENSE * DENSE
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mB, transposeB, beta, mC);
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// SPARSE * DENSE
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAsparse, transposeA, mB, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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// SPARSE * DENSE -> SPARSE
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beta = 1; // note that dense only allow beta == 1, while sparse CPU support arbitrary beta
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transposeA = false;
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transposeB = true; // only support !transposeA && tranposeB for Dense * CSC -> SBC
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Matrix<float> mA1sparseCSC(mAdense.DeepClone());
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mA1sparseCSC.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, true);
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Matrix<float> mA2dense(c_deviceIdZero);
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mA2dense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -300.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mA2sparseCSC(mA2dense.DeepClone());
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mA2sparseCSC.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, true);
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// dense for comparison
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mC.Resize(dim1, dim1);
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mC.SetValue(0.0f);
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Matrix<float>::MultiplyAndAdd(mAdense, transposeA, mAdense, transposeB, mC);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mA2dense, transposeB, beta, mC);
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// make sure (dense * sparse -> dense) == (dense * dense -> dense)
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mD.Resize(dim1, dim1);
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mD.SetValue(0.0f);
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Matrix<float>::MultiplyAndAdd(mAdense, transposeA, mA1sparseCSC, transposeB, mD);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mA2sparseCSC, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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// test on sparse
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mD.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
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Matrix<float>::MultiplyAndAdd(mAdense, transposeA, mA1sparseCSC, transposeB, mD);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mA2sparseCSC, transposeB, beta, mD);
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// copy mD to dense and compare
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Matrix<float> mE = Matrix<float>::Zeros(dim1, dim1, c_deviceIdZero);
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Matrix<float>::ScaleAndAdd(1, mD, mE);
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BOOST_CHECK(mE.IsEqualTo(mC, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(MatrixDenseTimesSparse, RandomSeedFixture)
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{
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, true);
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Matrix<float> mB = Matrix<float>::RandomGaussian(dim2, dim1, c_deviceIdZero, 1.0f, 4.0f, IncrementCounter());
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Matrix<float> mC = Matrix<float>::RandomGaussian(dim2, dim2, c_deviceIdZero, 1.0f, 2.0f, IncrementCounter());
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Matrix<float> mD(mC.DeepClone());
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bool transposeA = false, transposeB = false;
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float alpha = 0.3f;
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float beta = 0.0f;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAdense, transposeB, beta, mC);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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alpha = 3.3f;
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beta = 1.3f;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAdense, transposeB, beta, mC);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(CPUMatrixDenseTimesSparse, RandomSeedFixture)
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{
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Matrix<float> mAdense(CPUDEVICE);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, true);
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Matrix<float> mB = Matrix<float>::RandomGaussian(dim2, dim1, CPUDEVICE, 1, 4, IncrementCounter());
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Matrix<float> mC = Matrix<float>::RandomGaussian(dim2, dim2, CPUDEVICE, 1, 2, IncrementCounter());
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Matrix<float> mD(mC.DeepClone());
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bool transposeA = false, transposeB = false;
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float alpha = 0.3f;
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float beta = 0.0f;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAdense, transposeB, beta, mC);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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alpha = 3.3f;
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beta = 1.3f;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAdense, transposeB, beta, mC);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mD);
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BOOST_CHECK(mD.IsEqualTo(mC, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(CPUMatrixDenseTimesSparseAsSparse, RandomSeedFixture)
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{
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#if 0
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// TODO commented temporarily since 'IsEqualTo' is not yet implemented
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Matrix<float> mAdense(CPUDEVICE);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense);
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, true);
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Matrix<float> mB = Matrix<float>::RandomGaussian(dim1, dim2, 1, 4, IncrementCounter(), CPUDEVICE);
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Matrix<float> mC = Matrix<float>::RandomGaussian(dim1, dim1, 1, 2, IncrementCounter(), CPUDEVICE);
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Matrix<float> mDblock(CPUDEVICE);
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mDblock.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, true);
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float alpha = 0.3f;
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float beta = 1.2f;
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bool transposeA = false, transposeB = true;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mDblock);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mB, transposeA, mAsparse, transposeB, beta, mC);
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// TODO IsEqualTo not yet implemented for sparse block matrix
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// switch type from sparse block matrix is also not yet implemented
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// --> (mDblock.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, true);)
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BOOST_CHECK(mDblock.IsEqualTo(mC, c_epsilonFloatE4));
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#endif
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}
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BOOST_FIXTURE_TEST_CASE(MatrixSparseTimesSparse, RandomSeedFixture)
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{
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float> mBdense(c_deviceIdZero);
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mBdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim2, dim1, c_deviceIdZero, -5.0f, 0.4f, IncrementCounter()), 0);
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Matrix<float> mBsparse(mBdense.DeepClone());
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mBsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float> mCdense(c_deviceIdZero);
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mCdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim1, c_deviceIdZero, -4.0f, 0.2f, IncrementCounter()), 0);
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Matrix<float> mCsparse(mCdense.DeepClone());
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mCsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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bool transposeA = false, transposeB = false;
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float alpha = 2.4f;
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float beta = 0.0f;
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mBdense, transposeB, beta, mCdense);
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Matrix<float>::MultiplyAndWeightedAdd(alpha, mAsparse, transposeA, mBsparse, transposeB, beta, mCsparse);
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mCsparse.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, true);
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BOOST_CHECK(mCsparse.IsEqualTo(mCdense, c_epsilonFloatE4));
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// TODO: as soon as beta != 0.0 the 'MultiplyAndWeightedAdd' fails with stack overflow (also in the first test 5 lines above)
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// alpha = 2.4f;
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// beta = 3.4f;
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// mCsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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// Matrix<float>::MultiplyAndWeightedAdd(alpha, mAdense, transposeA, mBdense, transposeB, beta, mCdense);
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// Matrix<float>::MultiplyAndWeightedAdd(alpha, mAsparse, transposeA, mBsparse, transposeB, beta, mCsparse);
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// mCsparse.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, true);
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// BOOST_CHECK(mCsparse.IsEqualTo(mCdense, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(MatrixSparsePlusSparse, RandomSeedFixture)
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{
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std::mt19937 rng(0);
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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Matrix<float> mBdense(c_deviceIdZero);
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mBdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -5.0f, 0.4f, IncrementCounter()), 0);
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Matrix<float> mBsparse(mBdense.DeepClone());
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float alpha = 1.0f * rng() / rng.max();
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Matrix<float>::ScaleAndAdd(alpha, mAdense, mBdense);
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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mBsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float>::ScaleAndAdd(alpha, mAsparse, mBsparse);
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mBsparse.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, true);
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BOOST_CHECK(mBsparse.IsEqualTo(mBdense, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(MatrixDensePlusSparse, RandomSeedFixture)
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{
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std::mt19937 rng(0);
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mBdense(c_deviceIdZero);
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mBdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -5.0f, 0.4f, IncrementCounter()), 0);
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Matrix<float> mBsparse(mBdense.DeepClone());
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float alpha = 1.0f * rng() / rng.max();
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Matrix<float>::ScaleAndAdd(alpha, mAdense, mBdense);
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mBsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float>::ScaleAndAdd(alpha, mAdense, mBsparse);
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mBsparse.SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, true);
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BOOST_CHECK(mBsparse.IsEqualTo(mBdense, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(MatrixSparsePlusDense, RandomSeedFixture)
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{
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std::mt19937 rng(0);
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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Matrix<float> mBdense(c_deviceIdZero);
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mBdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -5.0f, 0.4f, IncrementCounter()), 0);
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Matrix<float> Bd1(mBdense.DeepClone());
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float alpha = 1.0f * rng() / rng.max();
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Matrix<float>::ScaleAndAdd(alpha, mAdense, mBdense);
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float>::ScaleAndAdd(alpha, mAsparse, Bd1);
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BOOST_CHECK(Bd1.IsEqualTo(mBdense, c_epsilonFloatE4));
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}
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BOOST_FIXTURE_TEST_CASE(MatrixSparseElementWisePower, RandomSeedFixture)
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{
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Matrix<float> mAdense(c_deviceIdZero);
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mAdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -3.0f, 0.1f, IncrementCounter()), 0);
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Matrix<float> mAsparse(mAdense.DeepClone());
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mAsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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Matrix<float> mBdense(c_deviceIdZero);
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mBdense.AssignTruncateBottomOf(Matrix<float>::RandomUniform(dim1, dim2, c_deviceIdZero, -5.0f, 0.4f, IncrementCounter()), 0);
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Matrix<float> mBsparse(mBdense.DeepClone());
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mBsparse.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSR, true);
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mAdense ^= 2.3f;
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mAsparse ^= 2.3f;
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// TODO randomly fails ....
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// BOOST_CHECK(mAsparse.IsEqualTo(mAdense, c_epsilonFloatE3));
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// BOOST_CHECK(mAdense.IsEqualTo(mAsparse, c_epsilonFloatE3));
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// mBdense.AssignElementPowerOf(mAdense, 3.2f);
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// mBsparse.AssignElementPowerOf(mAsparse, 3.2f);
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// BOOST_CHECK(mBsparse.IsEqualTo(mBdense, c_epsilonFloatE3));
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// BOOST_CHECK(mBdense.IsEqualTo(mBsparse, c_epsilonFloatE3));
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BOOST_CHECK(1);
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}
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BOOST_AUTO_TEST_SUITE_END()
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}
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} } }
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