// 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 { #define ELT(MATHOP) \ for (int n = 0; n < xn; n++) { \ for (int c = 0; c < xc; c++) { \ for (int h = 0; h < xh; h++) { \ for (int w = 0; w < xw; w++) { \ int x_offset = n * xc * xh * xw + c * xh * xw + h * xw + w; \ int y_offset = 0; \ if (yn != 1) y_offset += n * yc * yh * yw; \ if (yc != 1) y_offset += c * yh * yw; \ if (yh != 1) y_offset += h * yw; \ if (yw != 1) y_offset += w; \ out_data[x_offset] = out_data[x_offset] MATHOP y_data[y_offset]; \ } \ } \ } \ } class ElementwiseComputeTester : public arena::TestCase { protected: // common attributes for this op. std::string x_ = "x"; std::string y_ = "y"; std::string out_ = "out"; // add, sub, mul, div, max std::string elt_type_ = ""; DDim x_dims_{{1, 2, 3, 4}}; DDim y_dims_{{1, 2, 3, 4}}; int axis_ = 1; std::string act_type_ = ""; public: ElementwiseComputeTester(const Place& place, const std::string& alias, std::string elt_type = "add", std::vector x_shape = {1, 2, 3, 4}, std::vector y_shape = {1, 2, 3, 4}, int axis = 1, std::string act_type = "") : TestCase(place, alias), elt_type_(elt_type), x_dims_(DDim(x_shape)), y_dims_(DDim(y_shape)), axis_(axis), act_type_(act_type) {} void RunBaseline(Scope* scope) override { if (axis_ < 0) { axis_ = x_dims_.size() - y_dims_.size(); } auto x_shape = x_dims_.Vectorize(); while (x_shape.size() < 4) { x_shape.push_back(1); } auto y_shape = y_dims_.Vectorize(); y_shape.insert(y_shape.begin(), axis_, 1); while (y_shape.size() < 4) { y_shape.push_back(1); } CHECK_EQ(x_shape.size(), 4); CHECK_EQ(y_shape.size(), 4); auto x = scope->FindTensor(x_); auto y = scope->FindTensor(y_); auto x_data = x->data(); auto y_data = y->data(); auto out = scope->NewTensor(out_); out->Resize(x_dims_); auto out_data = out->mutable_data(); memcpy(out_data, x_data, sizeof(float) * x_dims_.production()); int xn = x_shape[0]; int xc = x_shape[1]; int xh = x_shape[2]; int xw = x_shape[3]; int yn = y_shape[0]; int yc = y_shape[1]; int yh = y_shape[2]; int yw = y_shape[3]; if (elt_type_ == "add") { ELT(+); } else if (elt_type_ == "sub") { ELT(-); } else if (elt_type_ == "mul") { ELT(*); } else if (elt_type_ == "div") { ELT(/); } else if (elt_type_ == "max") { for (int n = 0; n < xn; n++) { for (int c = 0; c < xc; c++) { for (int h = 0; h < xh; h++) { for (int w = 0; w < xw; w++) { int x_offset = n * xc * xh * xw + c * xh * xw + h * xw + w; int y_offset = 0; if (yn != 1) y_offset += n * yc * yh * yw; if (yc != 1) y_offset += c * yh * yw; if (yh != 1) y_offset += h * yw; if (yw != 1) y_offset += w; out_data[x_offset] = std::max(out_data[x_offset], y_data[y_offset]); } } } } } else { LOG(FATAL) << "unsupported"; } if (!act_type_.empty()) { if (act_type_ == "relu") { for (int i = 0; i < x_dims_.production(); i++) { out_data[i] = std::max(0.f, out_data[i]); } } else { LOG(FATAL) << "unsupported"; } } } void PrepareOpDesc(cpp::OpDesc* op_desc) { std::string op_type = "elementwise_" + elt_type_; if (!act_type_.empty()) { op_type = "fusion_" + op_type + "_activation"; } op_desc->SetType(op_type); op_desc->SetInput("X", {x_}); op_desc->SetInput("Y", {y_}); op_desc->SetOutput("Out", {out_}); op_desc->SetAttr("axis", axis_); if (!act_type_.empty()) { op_desc->SetAttr("act_type", act_type_); } } void PrepareData() override { std::vector dx(x_dims_.production()); for (size_t i = 0; i < dx.size(); i++) { dx[i] = (i % 3) * 1.1f; dx[i] = dx[i] == 0 ? 1.f : dx[i]; } SetCommonTensor(x_, x_dims_, dx.data()); std::vector dy(y_dims_.production()); for (size_t i = 0; i < dy.size(); i++) { dy[i] = (i % 5) * 1.1f; dy[i] = dy[i] == 0 ? 1.f : dy[i]; } SetCommonTensor(y_, y_dims_, dy.data()); } }; // add sub mul div max +act void TestElt(Place place, float abs_error, std::string elt_type, std::vector x_shape, std::vector y_shape, int axis, std::string act_type = "") { std::unique_ptr tester(new ElementwiseComputeTester( place, "def", elt_type, x_shape, y_shape, axis, act_type)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } void TestEltDims(Place place, float abs_error) { TestElt(place, abs_error, "add", {2, 3, 4, 5}, {2, 3, 4, 5}, 0); TestElt(place, abs_error, "add", {2, 3, 4}, {2, 3, 4}, 0); TestElt(place, abs_error, "add", {2, 3, 4}, {2, 3}, 0); TestElt(place, abs_error, "add", {2, 3}, {2}, 0); TestElt(place, abs_error, "add", {2, 3, 4, 5}, {3, 4}, 1); TestElt(place, abs_error, "add", {2, 3, 4}, {3, 4}, 1); TestElt(place, abs_error, "add", {2, 3}, {3}, 1); TestElt(place, abs_error, "add", {2, 3, 4, 5}, {4, 5}, 2); TestElt(place, abs_error, "add", {2, 3, 4}, {4}, 2); TestElt(place, abs_error, "add", {2, 3, 4, 5}, {5}, 3); TestElt(place, abs_error, "add", {2, 3, 4, 5}, {3, 4, 5}, -1); TestElt(place, abs_error, "add", {2, 3, 4}, {3, 4}, -1); } void TestEltTypes(Place place, float abs_error) { for (auto elt_type : std::vector{"add", "sub", "mul", "div", "max"}) { TestElt(place, abs_error, elt_type, {2, 3, 4, 5}, {2, 3, 4, 5}, 0); TestElt(place, abs_error, elt_type, {2, 3, 4, 5}, {3}, 1); } } void TestEltFuseAct(Place place, float abs_error) { for (auto elt_type : std::vector{"add", "sub", "mul", "div", "max"}) { TestElt(place, abs_error, elt_type, {2, 3, 4, 5}, {2, 3, 4, 5}, 0, "relu"); TestElt(place, abs_error, elt_type, {2, 3, 4, 5}, {3}, 1, "relu"); } } TEST(Elementwise, precision) { Place place; float abs_error = 2e-5; #if defined(LITE_WITH_NPU) place = TARGET(kNPU); abs_error = 1e-2; // use fp16 in npu #elif defined(LITE_WITH_ARM) place = TARGET(kARM); #elif defined(LITE_WITH_XPU) place = TARGET(kXPU); #else return; #endif // TestEltDims(place, abs_error); TestEltTypes(place, abs_error); TestEltFuseAct(place, abs_error); } } // namespace lite } // namespace paddle