// 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 #include #include "lite/api/paddle_use_kernels.h" #include "lite/api/paddle_use_ops.h" #include "lite/core/arena/framework.h" namespace paddle { namespace lite { enum activation_type_test { RELU, LEAKY_RELU, RELU_CLIPPED, PRELU, SIGMOID, TANH, SWISH, RELU6, LOG, EXP, FLOOR, RSQRT }; class ActivationComputeTester : public arena::TestCase { protected: // common attributes for this op. std::string input_ = "x"; std::string output_ = "out"; std::string prelu_alpha_ = "prelu_alpha"; float leaky_relu_alpha_ = 0.01; float relu_clipped_coef_ = 6.; std::string prelu_mode_ = ""; float swish_beta_ = 0.; DDim dims_{{1}}; std::string type_ = ""; activation_type_test act_type_ = RELU; public: ActivationComputeTester(const Place& place, const std::string& alias, float leaky_relu_alpha, float relu_clipped_coef, std::string prelu_mode, float swish_beta, DDim dims, std::string type, activation_type_test act_type) : TestCase(place, alias), leaky_relu_alpha_(leaky_relu_alpha), relu_clipped_coef_(relu_clipped_coef), prelu_mode_(prelu_mode), swish_beta_(swish_beta), dims_(dims), type_(type), act_type_(act_type) {} void RunBaseline(Scope* scope) override { auto* out = scope->NewTensor(output_); CHECK(out); out->Resize(dims_); auto* output_data = out->mutable_data(); auto* x = scope->FindTensor(input_); const auto* x_data = x->data(); switch (act_type_) { case RELU: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = std::max(0.f, x_data[i]); } break; } case LEAKY_RELU: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = x_data[i] > 0.f ? x_data[i] : x_data[i] * leaky_relu_alpha_; } break; } case RELU_CLIPPED: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = x_data[i] > 0.f ? x_data[i] : 0.f; output_data[i] = output_data[i] < relu_clipped_coef_ ? output_data[i] : relu_clipped_coef_; } break; } case PRELU: { auto* alpha = scope->FindTensor(prelu_alpha_); const auto* alpha_data = alpha->data(); int num = dims_[0]; int channel = dims_[1]; int csize = dims_[2] * dims_[3]; int bsize = channel * csize; if (prelu_mode_ == "all" || prelu_mode_ == "channel") { for (int n = 0; n < num; n++) { auto x_data_bptr = x_data + n * bsize; auto output_data_bptr = output_data + n * bsize; for (int c = 0; c < channel; c++) { auto x_data_cptr = x_data_bptr + c * csize; auto output_data_cptr = output_data_bptr + c * csize; float slope = prelu_mode_ == "all" ? alpha_data[0] : alpha_data[c]; for (int i = 0; i < csize; i++) { output_data_cptr[i] = x_data_cptr[i] > 0.f ? x_data_cptr[i] : x_data_cptr[i] * slope; } } } } else { for (int i = 0; i < dims_.production(); i++) { output_data[i] = x_data[i] > 0.f ? x_data[i] : x_data[i] * alpha_data[i]; } } break; } case SIGMOID: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = 1.f / (1.f + std::exp(-x_data[i])); } break; } case TANH: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = (std::exp(x_data[i]) - std::exp(-x_data[i])) / (std::exp(x_data[i]) + std::exp(-x_data[i])); } break; } case SWISH: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = x_data[i] / (1.f + std::exp(-swish_beta_ * x_data[i])); } break; } case RELU6: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = x_data[i] > 0.f ? x_data[i] : 0.f; output_data[i] = output_data[i] < 6.0 ? output_data[i] : 6.0; } break; } case LOG: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = std::log(x_data[i]); } break; } case EXP: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = std::exp(x_data[i]); } break; } case FLOOR: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = std::floor(x_data[i]); } break; } case RSQRT: { for (int i = 0; i < dims_.production(); i++) { output_data[i] = 1.0 / std::sqrt(x_data[i]); } break; } default: LOG(INFO) << "the type of activation is unknow."; } } void PrepareOpDesc(cpp::OpDesc* op_desc) { op_desc->SetType(type_); op_desc->SetInput("X", {input_}); op_desc->SetOutput("Out", {output_}); if (act_type_ == PRELU) { op_desc->SetInput("Alpha", {prelu_alpha_}); op_desc->SetAttr("mode", prelu_mode_); } if (act_type_ == LEAKY_RELU) { op_desc->SetAttr("alpha", leaky_relu_alpha_); } if (act_type_ == RELU_CLIPPED) { op_desc->SetAttr("Relu_clipped_coef", relu_clipped_coef_); } if (act_type_ == SWISH) { op_desc->SetAttr("beta", swish_beta_); } } void PrepareData() override { std::vector data(dims_.production()); for (int i = 0; i < dims_.production(); i++) { float sign = i % 3 == 0 ? -1.0f : 1.0f; sign = (type_ == "log" || type_ == "rsqrt") ? 1 : sign; data[i] = sign * static_cast(i % 128) * 0.013f + 0.001; } SetCommonTensor(input_, dims_, data.data()); if (type_ == "prelu") { int64_t alpha_len = 0; DDim alpha_dims; if (prelu_mode_ == "all") { alpha_len = 1; alpha_dims = DDim(std::vector({alpha_len})); } else if (prelu_mode_ == "channel") { alpha_len = dims_[1]; alpha_dims = DDim(std::vector({alpha_len})); } else if (prelu_mode_ == "element") { alpha_len = dims_.production(); alpha_dims = dims_; } std::vector prelu_alpha_data(alpha_len); for (int i = 0; i < alpha_len; i++) { float sign = i % 3 == 0 ? -1.0f : 1.0f; prelu_alpha_data[i] = sign * static_cast(i % 128) * 0.013f + 0.001; } SetCommonTensor(prelu_alpha_, alpha_dims, prelu_alpha_data.data()); } } }; TEST(Activation_relu, precision) { LOG(INFO) << "test relu op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto slope : {0.01, 0.1}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "relu", RELU)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_leaky_relu, precision) { LOG(INFO) << "test leaky_relu op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto slope : {0.01, 0.1}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", slope, 6., "all", 0., DDim(std::vector({n, c, h, w})), "leaky_relu", LEAKY_RELU)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_relu_clipped, precision) { LOG(INFO) << "test relu clipped op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto coef : {0.5, 6.}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, coef, "all", 0., DDim(std::vector({n, c, h, w})), "relu_clipped", RELU_CLIPPED)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_prelu, precision) { LOG(INFO) << "test prelu op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto mode : {"all", "channel", "element"}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6, mode, 0., DDim(std::vector({n, c, h, w})), "prelu", PRELU)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_sigmoid, precision) { LOG(INFO) << "test sigmoid op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "sigmoid", SIGMOID)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } TEST(Activation_tanh, precision) { LOG(INFO) << "test tanh op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "tanh", TANH)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } TEST(Activation_swish, precision) { LOG(INFO) << "test swish op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto coef : {0.01, 0.1}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6, "all", coef, DDim(std::vector({n, c, h, w})), "swish", SWISH)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_relu6, precision) { LOG(INFO) << "test relu6 op..."; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { for (auto slope : {0.01, 0.1}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "relu6", RELU6)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } } #endif } TEST(Activation_log, precision) { LOG(INFO) << "test log op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "log", LOG)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } TEST(Activation_exp, precision) { LOG(INFO) << "test exp op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "exp", EXP)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } TEST(Activation_floor, precision) { LOG(INFO) << "test floor op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {1, 3}) { for (auto c : {3, 6}) { for (auto h : {9, 18}) { for (auto w : {9, 18}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "floor", FLOOR)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } TEST(Activation_rsqrt, precision) { LOG(INFO) << "test rsqrt op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); for (auto n : {2}) { for (auto c : {2}) { for (auto h : {2}) { for (auto w : {2}) { std::unique_ptr tester(new ActivationComputeTester( place, "def", 0.01, 6., "all", 0., DDim(std::vector({n, c, h, w})), "rsqrt", RSQRT)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); } } } } #endif } } // namespace lite } // namespace paddle