// 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" namespace paddle { namespace lite { class CastComputeTester : public arena::TestCase { protected: // common attributes for this op. std::string input_ = "x"; std::string output_ = "out"; int in_dtype_; int out_dtype_; DDim x_dims_{{2, 2}}; public: CastComputeTester(const Place& place, const std::string& alias, int in_dtype, int out_dtype) : TestCase(place, alias), in_dtype_(in_dtype), out_dtype_(out_dtype) {} void RunBaseline(Scope* scope) override { auto* out = scope->NewTensor(output_); CHECK(out); out->Resize(x_dims_); if (out_dtype_ == 5 && in_dtype_ == 20) { auto* x = scope->FindTensor(input_); auto* x_data = x->data(); auto* output_data = out->mutable_data(); for (int i = 0; i < x_dims_.production(); i++) { *output_data = static_cast(*x_data); output_data++; x_data++; } } else if (out_dtype_ == 5 && in_dtype_ == 21) { auto* output_data = out->mutable_data(); auto* x = scope->FindTensor(input_); auto* x_data = x->data(); for (int i = 0; i < x_dims_.production(); i++) { *output_data = static_cast(*x_data); output_data++; x_data++; } } else if (out_dtype_ == 5 && in_dtype_ == 2) { auto* output_data = out->mutable_data(); auto* x = scope->FindTensor(input_); auto* x_data = x->data(); for (int i = 0; i < x_dims_.production(); i++) { *output_data = static_cast(*x_data); output_data++; x_data++; } } } void PrepareOpDesc(cpp::OpDesc* op_desc) { op_desc->SetType("cast"); op_desc->SetInput("X", {input_}); op_desc->SetOutput("Out", {output_}); op_desc->SetAttr("in_dtype", in_dtype_); op_desc->SetAttr("out_dtype", out_dtype_); } void PrepareData() override { SetPrecisionType(output_, PRECISION(kFloat)); if (in_dtype_ == 20) { std::vector x_data(x_dims_.production()); for (int i = 0; i < x_dims_.production(); i++) { x_data[i] = static_cast(i % 128); } SetCommonTensor(input_, x_dims_, x_data.data()); } else if (in_dtype_ == 21) { std::vector x_data(x_dims_.production()); for (int i = 0; i < x_dims_.production(); i++) { float sign = i % 3 == 0 ? -1.0f : 1.0f; x_data[i] = sign * static_cast(i % 128); } SetCommonTensor(input_, x_dims_, x_data.data()); } else if (in_dtype_ == 2) { std::vector x_data(x_dims_.production()); for (int i = 0; i < x_dims_.production(); i++) { int sign = i % 3 == 0 ? -1 : 1; x_data[i] = sign * static_cast(i % 128); } SetCommonTensor(input_, x_dims_, x_data.data()); } else { LOG(FATAL) << "not implemented!"; } } }; TEST(Cast, precision) { LOG(INFO) << "test cast op"; #ifdef LITE_WITH_ARM Place place(TARGET(kARM)); std::unique_ptr tester( new CastComputeTester(place, "def", 20, 5)); arena::Arena arena(std::move(tester), place, 2e-5); arena.TestPrecision(); std::unique_ptr tester1( new CastComputeTester(place, "def", 2, 5)); arena::Arena arena1(std::move(tester1), place, 2e-5); arena1.TestPrecision(); #endif } } // namespace lite } // namespace paddle