// 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. #include #include "lite/api/paddle_use_kernels.h" #include "lite/api/paddle_use_ops.h" #include "lite/core/arena/framework.h" #include "lite/tests/utils/fill_data.h" namespace paddle { namespace lite { class ScaleComputeTester : public arena::TestCase { protected: // common attributes for this op. std::string x_ = "x"; std::string out_ = "out"; DDim x_dims_{{100, 20}}; float scale_ = 0.; float bias_ = 0.; bool bias_after_scale_ = true; PrecisionType x_dtype_ = PRECISION(kFloat); public: ScaleComputeTester(const Place& place, const std::string& alias, const DDim& x_dims, float scale, float bias, bool bias_after_scale = true, PrecisionType x_dtype = PRECISION(kFloat)) : TestCase(place, alias), x_dims_(x_dims), scale_(scale), bias_(bias), bias_after_scale_(bias_after_scale), x_dtype_(x_dtype) {} template void RunBaselineHelper(Scope* scope) { auto* x = scope->FindTensor(x_); auto* x_data = x->data(); auto* out = scope->NewTensor(out_); out->Resize(x_dims_); T scale = static_cast(scale_); T bias = static_cast(bias_); if (!bias_after_scale_) { bias *= scale; } auto out_data = out->mutable_data(); for (int i = 0; i < x_dims_.production(); i++) { out_data[i] = x_data[i] * scale + bias; } } void RunBaseline(Scope* scope) override { switch (x_dtype_) { case PRECISION(kFloat): RunBaselineHelper(scope); break; case PRECISION(kInt32): RunBaselineHelper(scope); break; default: LOG(FATAL) << "unsupported data type: " << PrecisionToStr(x_dtype_); break; } } void PrepareOpDesc(cpp::OpDesc* op_desc) { op_desc->SetType("scale"); op_desc->SetInput("X", {x_}); op_desc->SetOutput("Out", {out_}); op_desc->SetAttr("scale", scale_); op_desc->SetAttr("bias", bias_); op_desc->SetAttr("bias_after_scale", bias_after_scale_); } template void PrepareDataHelper() { std::vector dx(x_dims_.production()); fill_data_rand(dx.data(), -10, 10, x_dims_.production()); SetCommonTensor(x_, x_dims_, dx.data()); } void PrepareData() override { switch (x_dtype_) { case PRECISION(kFloat): PrepareDataHelper(); break; case PRECISION(kInt32): PrepareDataHelper(); break; default: LOG(FATAL) << "unsupported data type: " << PrecisionToStr(x_dtype_); break; } } }; void TestScaleShape(Place place, float abs_error) { for (auto x_dims : std::vector>{{5, 2, 3, 4}, {8, 3, 5}, {12, 3}}) { std::unique_ptr tester( new ScaleComputeTester(place, "def", DDim(x_dims), 1.5f, 0.2f)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } } void TestScaleValue(Place place, float abs_error) { for (float scale : {0.123, 0., -1.2}) { for (float bias : {1., 0., -1.2331}) { std::unique_ptr tester(new ScaleComputeTester( place, "def", DDim({5, 2, 3, 4}), scale, bias)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } } } void TestScaleOrder(Place place, float abs_error) { for (bool bias_after_scale : {true, false}) { std::unique_ptr tester(new ScaleComputeTester( place, "def", DDim({2, 3, 4, 5}), 1.5f, 0.2f, bias_after_scale)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } } void TestScaleDtype(Place place, float abs_error) { for (PrecisionType x_dtype : {PRECISION(kFloat), PRECISION(kInt32)}) { if (x_dtype == PRECISION(kFloat)) { place.precision = PRECISION(kFloat); } else if (x_dtype == PRECISION(kInt32)) { place.precision = PRECISION(kInt32); } else { LOG(FATAL) << "fatal"; } std::unique_ptr tester(new ScaleComputeTester( place, "def", DDim({2, 3, 4, 5}), 2.f, 1.f, true, x_dtype)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } } TEST(Scale, precision) { Place place; float abs_error = 2e-5; #if defined(LITE_WITH_NPU) place = TARGET(kNPU); abs_error = 4e-3; // Using fp16 in NPU #elif defined(LITE_WITH_ARM) place = TARGET(kARM); #elif defined(LITE_WITH_XPU) && defined(LITE_WITH_XTCL) place = TARGET(kXPU); abs_error = 3e-4; // Some operations use fp16 in XPU #elif defined(LITE_WITH_X86) place = TARGET(kX86); #else return; #endif TestScaleShape(place, abs_error); TestScaleValue(place, abs_error); TestScaleOrder(place, abs_error); #ifdef LITE_WITH_ARM TestScaleDtype(place, abs_error); #endif } TEST(Scale, performance) { Place place; #if defined(LITE_WITH_ARM) place = TARGET(kARM); #elif defined(LITE_WITH_X86) place = TARGET(kX86); #else return; #endif std::unique_ptr tester(new ScaleComputeTester( place, "def", DDim(std::vector{5, 2, 3, 4}), 1.2, 1.1, true)); // To modify the arm context, one can retrive the context as follows. // #ifdef LITE_WITH_ARM // tester->context()->As(); // #endif arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPerformance(100); } } // namespace lite } // namespace paddle