/* 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. */ #include #include #include #include #include "gflags/gflags.h" #include "glog/logging.h" #include "gtest/gtest.h" #include "paddle/fluid/operators/jit/kernels.h" #include "paddle/fluid/platform/cpu_info.h" #include "paddle/fluid/platform/place.h" DEFINE_double(acc, 1e-5, "Test accuracy threshold."); template void RandomVec(const int n, T* a, const T lower = static_cast(-2.f), const T upper = static_cast(2.f)) { static unsigned int seed = 100; std::mt19937 rng(seed++); std::uniform_real_distribution uniform_dist(0, 1); for (int i = 0; i < n; ++i) { a[i] = static_cast(uniform_dist(rng) * (upper - lower) + lower); } } template void ExpectEQ(const T* target, const T* refer, size_t n) { if (std::is_floating_point::value) { for (size_t i = 0; i < n; ++i) { EXPECT_NEAR(target[i], refer[i], FLAGS_acc) << " at index : " << i; } } else { for (size_t i = 0; i < n; ++i) { EXPECT_EQ(target[i], refer[i]) << " at index : " << i; } } } std::vector TestSizes() { std::vector s; for (int i = 1; i < 32; ++i) { s.push_back(i); } // test some large size s.push_back(100); s.push_back(1000); s.push_back(2000); return s; } namespace jit = paddle::operators::jit; using CPUPlace = paddle::platform::CPUPlace; template struct TestFuncWithRefer { void operator()(const typename KernelTuples::func_type tgt, Args... args) { LOG(FATAL) << "Should specify this function."; } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector> { void operator()(const typename jit::XYZNTuples::func_type tgt, const std::vector& x, const std::vector& y, const std::vector& zref) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(zref.size(), x.size()); EXPECT_EQ(zref.size(), y.size()); const T* x_data = x.data(); const T* y_data = y.data(); const T* zref_data = zref.data(); const int d = zref.size(); std::vector ztgt(d); T* ztgt_data = ztgt.data(); // test normal tgt(x_data, y_data, ztgt_data, d); ExpectEQ(ztgt_data, zref_data, d); // test inplace x std::copy(x.begin(), x.end(), ztgt.begin()); tgt(ztgt_data, y_data, ztgt_data, d); ExpectEQ(ztgt_data, zref_data, d); // test inplace y std::copy(y.begin(), y.end(), ztgt.begin()); tgt(x_data, ztgt_data, ztgt_data, d); ExpectEQ(ztgt_data, zref_data, d); } }; template struct TestFuncWithRefer, T, std::vector, std::vector> { void operator()(const typename jit::AXYNTuples::func_type tgt, const T a, const std::vector& x, const std::vector& yref) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(yref.size(), x.size()); const T* x_data = x.data(); const T* yref_data = yref.data(); const int d = yref.size(); std::vector ytgt(d); T* ytgt_data = ytgt.data(); // test normal tgt(&a, x_data, ytgt_data, d); ExpectEQ(ytgt_data, yref_data, d); // test inplace x std::copy(x.begin(), x.end(), ytgt.begin()); tgt(&a, ytgt_data, ytgt_data, d); ExpectEQ(ytgt_data, yref_data, d); } }; template struct TestFuncWithRefer, std::vector, std::vector, int, int> { void operator()(const typename jit::SoftmaxTuples::func_type tgt, const std::vector& x, const std::vector& yref, int n, int bs) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(yref.size(), x.size()); EXPECT_EQ(x.size(), static_cast(n * bs)); const T* x_data = x.data(); const T* yref_data = yref.data(); std::vector ytgt(n * bs); T* ytgt_data = ytgt.data(); // test normal tgt(x_data, ytgt_data, n, bs); ExpectEQ(ytgt_data, yref_data, n * bs); // test inplace x std::copy(x.begin(), x.end(), ytgt.begin()); tgt(ytgt_data, ytgt_data, n, bs); ExpectEQ(ytgt_data, yref_data, n * bs); } }; template struct TestFuncWithRefer, std::vector, T> { void operator()(const typename jit::XRNTuples::func_type tgt, const std::vector& x, const T ref_res) { EXPECT_TRUE(tgt != nullptr); T tgt_res; tgt(x.data(), &tgt_res, x.size()); ExpectEQ(&tgt_res, &ref_res, 1); } }; template struct TestFuncWithRefer, std::vector, std::vector, int64_t, typename jit::VBroadcastTuples::attr_type> { void operator()(const typename jit::VBroadcastTuples::func_type tgt, const std::vector& x, const std::vector& yref, int64_t h, const typename jit::VBroadcastTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(x.size(), static_cast(attr)); EXPECT_EQ(yref.size(), x.size() * h); std::vector y(yref.size()); const T* x_data = x.data(); const T* yref_data = yref.data(); T* y_data = y.data(); tgt(x_data, y_data, h, attr); ExpectEQ(y_data, yref_data, yref.size()); } }; template struct TestFuncWithRefer, std::vector, std::vector> { void operator()(const typename jit::XYNTuples::func_type tgt, const std::vector& x, const std::vector& yref) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(yref.size(), x.size()); const T* x_data = x.data(); const T* yref_data = yref.data(); const int d = yref.size(); std::vector ytgt(d); T* ytgt_data = ytgt.data(); // test normal tgt(x_data, ytgt_data, d); ExpectEQ(ytgt_data, yref_data, d); // test inplace x std::copy(x.begin(), x.end(), ytgt.begin()); tgt(ytgt_data, ytgt_data, d); ExpectEQ(ytgt_data, yref_data, d); } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector, std::vector, std::vector, typename jit::LSTMTuples::attr_type> { void operator()(const typename jit::LSTMTuples::func_type tgt, const std::vector& xsrc, const std::vector& wp, const std::vector& ct_1, const std::vector& ct_ref, const std::vector& ht_ref, const typename jit::LSTMTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(ct_ref.size(), ht_ref.size()); EXPECT_EQ(ct_1.size(), ht_ref.size()); EXPECT_EQ(xsrc.size(), 4 * ht_ref.size()); EXPECT_EQ(wp.size(), 3 * ht_ref.size()); // x could be changed after compute, so copy to save src int d = ht_ref.size(); std::vector x(xsrc.size()), ct(ct_ref.size()), ht(ht_ref.size()); std::vector checked(2 * d); std::copy(xsrc.begin(), xsrc.end(), x.begin()); const T* ct_1_data = ct_1.data(); const T* wp_data = wp.data(); const T* ct_ref_data = ct_ref.data(); const T* ht_ref_data = ht_ref.data(); T* x_data = x.data(); T* ct_data = ct.data(); T* ht_data = ht.data(); T* checked_data = checked.data(); jit::lstm_t step; step.gates = x_data; step.ct_1 = ct_1_data; step.ct = ct_data; step.ht = ht_data; if (attr.use_peephole) { step.wp = wp_data; step.checked = checked_data; } tgt(&step, &attr); ExpectEQ(ct_data, ct_ref_data, d); ExpectEQ(ht_data, ht_ref_data, d); } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector, typename jit::GRUTuples::attr_type> { void operator()(const typename jit::GRUTuples::func_type tgt, const std::vector& xsrc, const std::vector& ht_1, const std::vector& ht_ref, const typename jit::GRUTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(ht_1.size(), ht_ref.size()); EXPECT_EQ(xsrc.size(), 3 * ht_ref.size()); // x could be changed after compute, so copy to save src int d = ht_ref.size(); std::vector x(xsrc.size()), ht(ht_ref.size()); std::copy(xsrc.begin(), xsrc.end(), x.begin()); const T* ht_1_data = ht_1.data(); const T* ht_ref_data = ht_ref.data(); T* x_data = x.data(); T* ht_data = ht.data(); jit::gru_t step; step.gates = x_data; step.ht_1 = ht_1_data; step.ht = ht_data; tgt(&step, &attr); ExpectEQ(ht_data, ht_ref_data, d); } }; template struct TestFuncWithRefer, std::vector, std::vector, typename jit::SeqPoolTuples::attr_type> { void operator()(const typename jit::SeqPoolTuples::func_type tgt, const std::vector& x, const std::vector& yref, const typename jit::SeqPoolTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(x.size() % yref.size(), static_cast(0)); int w = yref.size(); std::vector y(w); const T* x_data = x.data(); const T* yref_data = yref.data(); T* y_data = y.data(); tgt(x_data, y_data, &attr); ExpectEQ(y_data, yref_data, w); } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector, typename jit::EmbSeqPoolTuples::attr_type> { void operator()(const typename jit::EmbSeqPoolTuples::func_type tgt, const std::vector& table, const std::vector& idx, const std::vector& oref, const typename jit::EmbSeqPoolTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(table.size(), static_cast(attr.table_height * attr.table_width)); EXPECT_EQ(idx.size(), static_cast(attr.index_height * attr.index_width)); EXPECT_EQ(oref.size(), static_cast(attr.table_width * attr.index_width)); const T* table_data = table.data(); const int64_t* idx_data = idx.data(); const T* oref_data = oref.data(); int o_w = oref.size(); std::vector out(o_w); T* o_data = out.data(); tgt(table_data, idx_data, o_data, &attr); ExpectEQ(o_data, oref_data, o_w); } }; template struct TestFuncWithRefer, T, std::vector, std::vector, std::vector, std::vector, typename jit::SgdTuples::attr_type> { void operator()(const typename jit::SgdTuples::func_type tgt, const T lr, const std::vector& param, const std::vector& grad, const std::vector& rows, const std::vector& oref, const typename jit::SgdTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(param.size(), static_cast(attr.param_height * attr.param_width)); EXPECT_EQ(grad.size(), static_cast(attr.grad_height * attr.grad_width)); EXPECT_EQ(rows.size(), static_cast(attr.selected_rows_size)); EXPECT_EQ(param.size(), oref.size()); const T* param_data = param.data(); const T* grad_data = grad.data(); const int64_t* rows_data = rows.data(); const T* oref_data = oref.data(); std::vector out(oref.size()); T* o_data = out.data(); tgt(&lr, param_data, grad_data, rows_data, o_data, &attr); // only the selected rows should be equal for (size_t i = 0; i < rows.size(); ++i) { ExpectEQ(o_data + rows[i] * attr.grad_width, oref_data + rows[i] * attr.grad_width, attr.grad_width); } // inplace std::copy(param.begin(), param.end(), out.begin()); tgt(&lr, o_data, grad_data, rows_data, o_data, &attr); for (size_t i = 0; i < rows.size(); ++i) { ExpectEQ(o_data + rows[i] * attr.grad_width, oref_data + rows[i] * attr.grad_width, attr.grad_width); } } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector, typename jit::MatMulTuples::attr_type> { void operator()(const typename jit::MatMulTuples::func_type tgt, const std::vector& a, const std::vector& b, const std::vector& cref, const typename jit::MatMulTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(a.size(), static_cast(attr.m * attr.k)); EXPECT_EQ(b.size(), static_cast(attr.k * attr.n)); EXPECT_EQ(cref.size(), static_cast(attr.m * attr.n)); std::vector c(cref.size()); const T* a_data = a.data(); const T* b_data = b.data(); const T* cref_data = cref.data(); T* c_data = c.data(); tgt(a_data, b_data, c_data, &attr); ExpectEQ(c_data, cref_data, attr.m * attr.n); } }; template struct TestFuncWithRefer, std::vector, std::vector, std::vector, std::vector, std::vector, std::vector, int, float, int> { void operator()(const typename jit::LayerNormTuples::func_type tgt, std::vector& x, std::vector& outref, // NOLINT std::vector& mean, std::vector& var, // NOLINT const std::vector& scale, const std::vector& bias, int left, const float epsilon, int right) { EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(x.size(), static_cast(left * right)); EXPECT_EQ(outref.size(), static_cast(left * right)); EXPECT_EQ(mean.size(), static_cast(left)); EXPECT_EQ(var.size(), static_cast(left)); EXPECT_EQ(scale.size(), static_cast(right)); EXPECT_EQ(bias.size(), static_cast(right)); std::vector outtgt(outref.size()); const T* scale_data = scale.data(); const T* bias_data = bias.data(); T* x_data = x.data(); T* mean_data = mean.data(); T* var_data = var.data(); T* outref_data = outref.data(); T* outtgt_data = outtgt.data(); tgt(x_data, outtgt_data, mean_data, var_data, scale_data, bias_data, left, epsilon, right); ExpectEQ(outtgt_data, outref_data, left * right); } }; template struct TestFuncWithRefer, int, std::vector, std::vector, std::vector, std::vector, int> { void operator()(const typename jit::CRFDecodingTuples::func_type tgt, const int seq_len, const std::vector& x, const std::vector& w, std::vector& alpharef, // NOLINT std::vector& trackref, int tag_num) { // NOLINT constexpr int state_trans_base_idx = 2; EXPECT_TRUE(tgt != nullptr); EXPECT_EQ(x.size(), static_cast(seq_len * tag_num)); EXPECT_EQ(w.size(), static_cast((tag_num + state_trans_base_idx) * tag_num)); EXPECT_EQ(alpharef.size(), static_cast(seq_len * tag_num)); EXPECT_EQ(trackref.size(), static_cast(seq_len * tag_num)); std::vector alphatgt(alpharef.size()); std::vector tracktgt(trackref.size()); memcpy(trackref.data(), tracktgt.data(), tag_num * sizeof(int)); tgt(seq_len, (const T*)x.data(), (const T*)w.data(), alphatgt.data(), tracktgt.data(), tag_num); ExpectEQ(alpharef.data(), alphatgt.data(), seq_len * tag_num); ExpectEQ(trackref.data(), tracktgt.data(), seq_len * tag_num); } }; template void TestAllImpls(const typename KernelTuples::attr_type& attr, Args... args) { TestFuncWithRefer test; // test jitcode auto jitcode = jit::GetJitCode(attr); if (jitcode) { VLOG(10) << "Test Jitcode Kernel "; test(jitcode, args...); } // test all impls in more jit::KernelKey kkey(KT, PlaceType()); auto& pool = jit::KernelPool().Instance().AllKernels(); auto iter = pool.find(kkey); if (iter != pool.end()) { auto& impls = iter->second; for (auto& impl : impls) { auto i = dynamic_cast*>(impl.get()); if (i && i->UseMe(attr)) { auto more = i->GetFunc(); VLOG(10) << "Test More Kernel : " << i->ImplType(); test(more, args...); } } } // test result from Get function // VLOG(10) << "Test Get function "; auto tgt = jit::Get(attr); test(tgt, args...); } template void TestKernelXYZNTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); for (int d : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector x(d), y(d), zref(d); RandomVec(d, x.data()); RandomVec(d, y.data()); std::vector xinp(d), yinp(d); // inplace test std::copy(x.begin(), x.end(), xinp.begin()); std::copy(y.begin(), y.end(), yinp.begin()); const T* x_data = x.data(); const T* y_data = y.data(); T* zref_data = zref.data(); T* xinp_data = xinp.data(); T* yinp_data = yinp.data(); // test refer code inplace ref(x_data, y_data, zref_data, d); ref(x_data, yinp_data, yinp_data, d); ref(xinp_data, y_data, xinp_data, d); ExpectEQ(xinp_data, zref_data, d); ExpectEQ(yinp_data, zref_data, d); TestAllImpls, PlaceType, std::vector, std::vector, std::vector>(d, x, y, zref); } } template void TestKernelAXYNTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); for (int d : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); const T a = static_cast(3); std::vector x(d), yref(d); std::vector xinp(d); // inplace test RandomVec(d, x.data()); std::copy(x.begin(), x.end(), xinp.begin()); const T* x_data = x.data(); T* yref_data = yref.data(); T* xinp_data = xinp.data(); // test refer code inplace ref(&a, x_data, yref_data, d); ref(&a, xinp_data, xinp_data, d); ExpectEQ(xinp_data, yref_data, d); TestAllImpls, PlaceType, T, std::vector, std::vector>(d, a, x, yref); } } template void TestKernelXRNTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); auto last_acc = FLAGS_acc; FLAGS_acc = 1e-4; for (int d : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector x(d); RandomVec(d, x.data()); T ref_res; ref(x.data(), &ref_res, d); TestAllImpls, PlaceType, std::vector, T>(d, x, ref_res); } FLAGS_acc = last_acc; } template void TestKernelXYNTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); for (int d : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector x(d), yref(d); std::vector xinp(d); // inplace test RandomVec(d, x.data()); std::copy(x.begin(), x.end(), xinp.begin()); const T* x_data = x.data(); T* yref_data = yref.data(); T* xinp_data = xinp.data(); // test refer code inplace ref(x_data, yref_data, d); ref(xinp_data, xinp_data, d); ExpectEQ(xinp_data, yref_data, d); TestAllImpls, PlaceType, std::vector, std::vector>(d, x, yref); } } template void TestKernelLSTMTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); std::vector all_acts = {"sigmoid", "tanh", "relu", "identity"}; auto test_sizes = TestSizes(); test_sizes.erase(std::remove(test_sizes.begin(), test_sizes.end(), 1000)); for (int d : test_sizes) { for (bool use_peephole : {true, false}) { for (auto& act_gate : all_acts) { for (auto& act_cand : all_acts) { for (auto& act_cell : all_acts) { const jit::lstm_attr_t attr( d, jit::to_kerneltype(act_gate), jit::to_kerneltype(act_cand), jit::to_kerneltype(act_cell), use_peephole); auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector xsrc(4 * d), wp(3 * d), ct_1(d); std::vector ct_ref(d), ht_ref(d), checked(2 * d); RandomVec(4 * d, xsrc.data()); RandomVec(3 * d, wp.data(), -1.f, 1.f); RandomVec(d, ct_1.data(), -1.f, 1.f); // x could be changed after compute, so copy to save src std::vector x(xsrc.size()); std::copy(xsrc.begin(), xsrc.end(), x.begin()); const T* ct_1_data = ct_1.data(); const T* wp_data = wp.data(); T* x_data = x.data(); T* checked_data = checked.data(); T* ct_ref_data = ct_ref.data(); T* ht_ref_data = ht_ref.data(); jit::lstm_t step; step.gates = x_data; step.ct_1 = ct_1_data; step.ct = ct_ref_data; step.ht = ht_ref_data; if (use_peephole) { step.wp = wp_data; step.checked = checked_data; } ref(&step, &attr); VLOG(10) << attr; TestAllImpls, PlaceType, std::vector, std::vector, std::vector, std::vector, std::vector>(attr, xsrc, wp, ct_1, ct_ref, ht_ref, attr); } } } } } } template void TestKernelGRUTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); std::vector all_acts = {"sigmoid", "tanh", "relu", "identity"}; auto test_sizes = TestSizes(); test_sizes.erase(std::remove(test_sizes.begin(), test_sizes.end(), 1000)); for (int d : test_sizes) { for (auto& act_gate : all_acts) { for (auto& act_cand : all_acts) { const jit::gru_attr_t attr(d, jit::to_kerneltype(act_gate), jit::to_kerneltype(act_cand)); auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector xsrc(3 * d), ht_1(d), ht_ref(d); RandomVec(3 * d, xsrc.data()); RandomVec(d, ht_1.data()); // x could be changed after compute, so copy to save src std::vector x(xsrc.size()); std::copy(xsrc.begin(), xsrc.end(), x.begin()); const T* ht_1_data = ht_1.data(); T* x_data = x.data(); T* ht_ref_data = ht_ref.data(); jit::gru_t step; step.gates = x_data; step.ht_1 = ht_1_data; step.ht = ht_ref_data; ref(&step, &attr); VLOG(10) << attr; TestAllImpls, PlaceType, std::vector, std::vector, std::vector>(attr, xsrc, ht_1, ht_ref, attr); } } } } template void TestKernelSeqPoolTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); std::vector pool_types = { jit::SeqPoolType::kSum, jit::SeqPoolType::kAvg, jit::SeqPoolType::kSqrt}; auto test_sizes = TestSizes(); test_sizes.erase(std::remove(test_sizes.begin(), test_sizes.end(), 1000)); for (auto type : pool_types) { for (int w : test_sizes) { jit::seq_pool_attr_t attr(w, type); for (int h : test_sizes) { attr.h = h; auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector x(h * w), yref(w); RandomVec(h * w, x.data()); const T* x_data = x.data(); T* yref_data = yref.data(); ref(x_data, yref_data, &attr); VLOG(10) << attr; TestAllImpls, PlaceType, std::vector, std::vector>(attr, x, yref, attr); } } } } template void TestKernelMatMulTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); auto last_acc = FLAGS_acc; // export MKL_CBWR=AVX would make MKL force to use AVX // export KMP_DETERMINISTIC_REDUCTION=yes would make the result deterministic FLAGS_acc = 1e-3; for (int m : {1, 2, 3, 4}) { for (int n : {1, 2, 3, 4}) { for (int k : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector a(m * k), b(k * n), c(m * n); RandomVec(m * k, a.data()); RandomVec(k * n, b.data()); const T* a_data = a.data(); const T* b_data = b.data(); T* c_data = c.data(); const jit::matmul_attr_t attr{m, n, k}; ref(a_data, b_data, c_data, &attr); TestAllImpls, PlaceType, std::vector, std::vector, std::vector>(attr, a, b, c, attr); } } } FLAGS_acc = last_acc; } template void TestKernelSoftmaxTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); for (int bs : {1, 2, 10}) { for (int n : TestSizes()) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector x(bs * n), y(bs * n); RandomVec(bs * n, x.data()); const T* x_data = x.data(); T* y_data = y.data(); std::vector xinp(x.size()); // inplace test std::copy(x.begin(), x.end(), xinp.begin()); ref(x_data, y_data, n, bs); T* xinp_data = xinp.data(); ref(xinp_data, xinp_data, n, bs); ExpectEQ(xinp_data, y_data, n * bs); TestAllImpls, PlaceType, std::vector, std::vector>(n, x, y, n, bs); } } } template void TestKernelEmbSeqPoolTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); int64_t tbl_h = 1e4; std::vector pool_types = { jit::SeqPoolType::kSum}; // only support sum yet auto test_sizes = TestSizes(); test_sizes.erase(std::remove(test_sizes.begin(), test_sizes.end(), 1000)); for (int tbl_w : test_sizes) { std::vector table(tbl_h * tbl_w); RandomVec(tbl_h * tbl_w, table.data()); const T* table_data = table.data(); for (auto type : pool_types) { for (int idx_w : {1, 2, 10, 16}) { for (int idx_h : {1, 2, 9, 13, 16}) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector idx(idx_h * idx_w); RandomVec(idx_h * idx_w, idx.data(), 0, tbl_h - 1); int64_t out_w = tbl_w * idx_w; std::vector oref(out_w); const int64_t* idx_data = idx.data(); T* o_data = oref.data(); jit::emb_seq_pool_attr_t attr(tbl_h, tbl_w, idx_h, idx_w, out_w, type); ref(table_data, idx_data, o_data, &attr); TestAllImpls, PlaceType, std::vector, std::vector, std::vector>(attr, table, idx, oref, attr); } } } } } template void TestKernelSgdTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); const T lr = 0.1; auto UnDuplicatedRandomVec = [](int n, const int64_t lower, const int64_t upper) -> std::vector { PADDLE_ENFORCE_LE(static_cast(upper - lower), n - 1); PADDLE_ENFORCE_GT(n, 0); std::vector all, out; for (int i = 0; i < n; ++i) { all.push_back(i); } std::random_shuffle(all.begin(), all.end()); out.insert(out.begin(), all.begin(), all.begin() + n); return out; }; for (int param_h : {1, 10}) { for (int grad_w : TestSizes()) { std::vector param(param_h * grad_w); std::vector param_out(param_h * grad_w); RandomVec(param_h * grad_w, param.data()); const T* param_data = param.data(); T* out_data = param_out.data(); for (int rows_size = 1; rows_size <= param_h; ++rows_size) { std::vector grad(rows_size * grad_w); std::vector rows = UnDuplicatedRandomVec(rows_size, 0, rows_size - 1); RandomVec(rows_size * grad_w, grad.data()); const int64_t* rows_data = rows.data(); const T* grad_data = grad.data(); auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); jit::sgd_attr_t attr(param_h, grad_w, rows_size, grad_w, rows_size); ref(&lr, param_data, grad_data, rows_data, out_data, &attr); // inplace test std::vector inp(param.size()); std::copy(param.begin(), param.end(), inp.begin()); T* inp_data = inp.data(); ref(&lr, inp_data, grad_data, rows_data, inp_data, &attr); // only the selected rows should be equal for (int i = 0; i < rows_size; ++i) { ExpectEQ(inp_data + rows[i] * grad_w, out_data + rows[i] * grad_w, grad_w); } TestAllImpls, PlaceType, T, std::vector, std::vector, std::vector, std::vector>( attr, lr, param, grad, rows, param_out, attr); } } } } template void TestKernelNCHW16CMulNCTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); const int n = 3, c = 16 * 4, h = 10, w = 10; auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); int sz = n * c * h * w; std::vector x(sz), y(n * c), zref(sz); std::vector ztgt(sz), zjit(sz); RandomVec(sz, x.data()); RandomVec(n * c, y.data()); const T* x_data = x.data(); const T* y_data = y.data(); T* zref_data = zref.data(); T* ztgt_data = ztgt.data(); T* zjit_data = zjit.data(); constexpr int simd_width = ZMM_FLOAT_BLOCK; int C = c / simd_width; auto tgt = jit::Get, PlaceType>(0); auto jitcode = jit::GetJitCode, PlaceType>(0); EXPECT_TRUE(tgt != nullptr); if (std::is_same::value && paddle::platform::MayIUse(paddle::platform::avx512f)) { EXPECT_TRUE(jitcode != nullptr); } for (int ni = 0; ni < n; ni++) { for (int ci = 0; ci < C; ci++) { auto ptr_x = x_data + ni * C * h * w * simd_width + ci * h * w * simd_width; auto ptr_y = y_data + ni * C * simd_width + ci * simd_width; auto ptr_zref = zref_data + ni * C * h * w * simd_width + ci * h * w * simd_width; auto ptr_ztgt = ztgt_data + ni * C * h * w * simd_width + ci * h * w * simd_width; ref(ptr_x, ptr_y, ptr_zref, h, w); tgt(ptr_x, ptr_y, ptr_ztgt, h, w); if (jitcode) { auto ptr_zjit = zjit_data + ni * C * h * w * simd_width + ci * h * w * simd_width; jitcode(ptr_x, ptr_y, ptr_zjit, h, w); } } } ExpectEQ(ztgt_data, zref_data, sz); if (jitcode) { ExpectEQ(zjit_data, zref_data, sz); } } template void TestKernelLayerNormTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); const T epsilon = 9.99999975e-06; for (int n : {1, 2, 10}) { for (int x_dim_0 : {1, 9, 17, 50}) { int left = n * x_dim_0; for (int x_dim_1 : TestSizes()) { int right = x_dim_1; auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); int sz = left * right; std::vector x(sz), mean(left), var(left), scale(right), bias(right), outref(sz); RandomVec(sz, x.data()); RandomVec(left, mean.data()); RandomVec(left, var.data()); RandomVec(right, scale.data()); RandomVec(right, bias.data()); const T* scale_data = scale.data(); const T* bias_data = bias.data(); T* x_data = x.data(); T* mean_data = mean.data(); T* var_data = var.data(); T* outref_data = outref.data(); ref(x_data, outref_data, mean_data, var_data, scale_data, bias_data, left, epsilon, right); TestAllImpls, PlaceType, std::vector, std::vector, std::vector, std::vector, std::vector, std::vector, int, float>( right, x, outref, mean, var, scale, bias, left, epsilon, right); } } } } template void TestKernelCRFDecodingTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); constexpr int state_trans_base_idx = 2; auto test_sizes = TestSizes(); test_sizes.erase(std::remove(test_sizes.begin(), test_sizes.end(), 2000)); for (int seq_len : {1, 11, 17, 50}) { for (int tag_num : test_sizes) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); int x_sz = seq_len * tag_num; int w_sz = (tag_num + state_trans_base_idx) * tag_num; std::vector x(x_sz), w(w_sz), alpharef(x_sz); std::vector trackref(x_sz); RandomVec(x_sz, x.data()); RandomVec(w_sz, w.data()); ref(seq_len, (const T*)x.data(), (const T*)w.data(), alpharef.data(), trackref.data(), tag_num); TestAllImpls, PlaceType, int, std::vector, std::vector, std::vector, std::vector, int>(tag_num, seq_len, x, w, alpharef, trackref, tag_num); } } } template void TestKernelVBroadcastTuples() { VLOG(10) << "===== Test JITKernel " << jit::to_string(KT); for (int w : TestSizes()) { std::vector x(w); RandomVec(w, x.data()); const T* x_data = x.data(); for (int64_t h : {1, 2, 6}) { auto ref = jit::GetRefer>(); EXPECT_TRUE(ref != nullptr); std::vector y(w * h); T* y_data = y.data(); ref(x_data, y_data, h, w); TestAllImpls, PlaceType, std::vector, std::vector, int64_t>(static_cast(w), x, y, h, static_cast(w)); } } } #define TEST_CPU_KERNEL(test_tuple, kernel_type) \ TEST(JITKernel, kernel_type) { \ TestKernel##test_tuple(); \ TestKernel##test_tuple(); \ } TEST_CPU_KERNEL(XYZNTuples, kVMul); TEST_CPU_KERNEL(XYZNTuples, kVAdd); TEST_CPU_KERNEL(XYZNTuples, kVAddRelu); TEST_CPU_KERNEL(XYZNTuples, kVSub); TEST_CPU_KERNEL(AXYNTuples, kVScal); TEST_CPU_KERNEL(AXYNTuples, kVAddBias); TEST_CPU_KERNEL(XRNTuples, kHMax); TEST_CPU_KERNEL(XRNTuples, kHSum); TEST_CPU_KERNEL(XYNTuples, kVRelu); TEST_CPU_KERNEL(XYNTuples, kVIdentity); TEST_CPU_KERNEL(XYNTuples, kVSquare); TEST_CPU_KERNEL(XYNTuples, kVExp); TEST_CPU_KERNEL(XYNTuples, kVSigmoid); TEST_CPU_KERNEL(XYNTuples, kVTanh); TEST_CPU_KERNEL(XYNTuples, kVCopy); TEST_CPU_KERNEL(LSTMTuples, kLSTMCtHt); TEST_CPU_KERNEL(LSTMTuples, kLSTMC1H1); TEST_CPU_KERNEL(GRUTuples, kGRUH1); TEST_CPU_KERNEL(GRUTuples, kGRUHtPart1); TEST_CPU_KERNEL(GRUTuples, kGRUHtPart2); TEST_CPU_KERNEL(NCHW16CMulNCTuples, kNCHW16CMulNC); TEST_CPU_KERNEL(SeqPoolTuples, kSeqPool); TEST_CPU_KERNEL(MatMulTuples, kMatMul); TEST_CPU_KERNEL(SoftmaxTuples, kSoftmax); TEST_CPU_KERNEL(EmbSeqPoolTuples, kEmbSeqPool); TEST_CPU_KERNEL(SgdTuples, kSgd); TEST_CPU_KERNEL(LayerNormTuples, kLayerNorm); TEST_CPU_KERNEL(CRFDecodingTuples, kCRFDecoding); TEST_CPU_KERNEL(VBroadcastTuples, kVBroadcast); TEST(JITKernel_key, lstm) { jit::lstm_attr_t attr1(8, jit::kVIdentity, jit::kVSigmoid, jit::kVTanh); jit::lstm_attr_t attr2(9, jit::kVIdentity, jit::kVSigmoid, jit::kVTanh); jit::lstm_attr_t attr3(9, jit::kVIdentity, jit::kVSigmoid, jit::kVTanh); jit::lstm_attr_t attr4(9, jit::kVRelu, jit::kVSigmoid, jit::kVTanh); auto key1 = jit::JitCodeKey(attr1); auto key2 = jit::JitCodeKey(attr2); auto key3 = jit::JitCodeKey(attr3); auto key4 = jit::JitCodeKey(attr4); EXPECT_TRUE(key1 != key2); EXPECT_TRUE(key2 == key3); EXPECT_TRUE(key3 != key4); } TEST(JITKernel_key, gru) { jit::gru_attr_t attr1(8, jit::kVSigmoid, jit::kVTanh); jit::gru_attr_t attr2(9, jit::kVSigmoid, jit::kVTanh); jit::gru_attr_t attr3(9, jit::kVSigmoid, jit::kVTanh); jit::gru_attr_t attr4(9, jit::kVSigmoid, jit::kVIdentity); auto key1 = jit::JitCodeKey(attr1); auto key2 = jit::JitCodeKey(attr2); auto key3 = jit::JitCodeKey(attr3); auto key4 = jit::JitCodeKey(attr4); EXPECT_TRUE(key1 != key2); EXPECT_TRUE(key2 == key3); EXPECT_TRUE(key3 != key4); } // TODO(TJ): add more test about key and pool