// 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: std::string x_ = "x"; std::string out_ = "out"; // BOOL = 0;INT16 = 1;INT32 = 2;INT64 = 3;FP16 = 4;FP32 = 5;FP64 = 6; // SIZE_T = 19;UINT8 = 20;INT8 = 21; int in_dtype_; int out_dtype_; DDim 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) {} template void RunBaselineHelper(Scope* scope) { auto* x = scope->FindTensor(x_); auto* x_data = x->data(); auto* out = scope->NewTensor(out_); CHECK(out); out->Resize(dims_); auto* out_data = out->mutable_data(); for (int i = 0; i < dims_.production(); i++) { *out_data = static_cast(*x_data); out_data++; x_data++; } } void RunBaseline(Scope* scope) override { if (in_dtype_ == 20 && out_dtype_ == 5) { RunBaselineHelper(scope); } else if (in_dtype_ == 2 && out_dtype_ == 5) { RunBaselineHelper(scope); } else if (in_dtype_ == 3 && out_dtype_ == 5) { RunBaselineHelper(scope); } else if (in_dtype_ == 5 && out_dtype_ == 3) { RunBaselineHelper(scope); } else if (in_dtype_ == 21 && out_dtype_ == 5) { RunBaselineHelper(scope); } else if (in_dtype_ == 5 && out_dtype_ == 21) { RunBaselineHelper(scope); } else { LOG(FATAL) << "unsupported"; } } void PrepareOpDesc(cpp::OpDesc* op_desc) { op_desc->SetType("cast"); op_desc->SetInput("X", {x_}); op_desc->SetOutput("Out", {out_}); op_desc->SetAttr("in_dtype", in_dtype_); op_desc->SetAttr("out_dtype", out_dtype_); } template void PrepareDataHelper() { std::vector x_data(dims_.production()); for (int i = 0; i < dims_.production(); i++) { x_data[i] = static_cast(i % 128); } SetCommonTensor(x_, dims_, x_data.data()); } void PrepareData() override { // BOOL = 0;INT16 = 1;INT32 = 2;INT64 = 3;FP16 = 4;FP32 = 5;FP64 = 6; // SIZE_T = 19;UINT8 = 20;INT8 = 21; switch (in_dtype_) { case 20: PrepareDataHelper(); break; case 21: PrepareDataHelper(); break; case 1: PrepareDataHelper(); break; case 2: PrepareDataHelper(); break; case 3: PrepareDataHelper(); break; case 5: PrepareDataHelper(); break; case 6: PrepareDataHelper(); break; case 19: PrepareDataHelper(); break; default: LOG(FATAL) << "unsupported data type: " << in_dtype_; break; } } }; void TestCast(Place place, float abs_error, int in_dtype, int out_dtype) { std::unique_ptr tester( new CastComputeTester(place, "def", in_dtype, out_dtype)); arena::Arena arena(std::move(tester), place, abs_error); arena.TestPrecision(); } TEST(Cast, precision) { Place place; float abs_error = 2e-5; #if defined(LITE_WITH_ARM) place = TARGET(kARM); #elif defined(LITE_WITH_XPU) && defined(LITE_WITH_XTCL) place = TARGET(kXPU); #elif defined(LITE_WITH_HUAWEI_ASCEND_NPU) place = TARGET(kHuaweiAscendNPU); abs_error = 1e-2; // precision_mode default is force_fp16 #else return; #endif // BOOL = 0;INT16 = 1;INT32 = 2;INT64 = 3;FP16 = 4;FP32 = 5;FP64 = 6; // SIZE_T = 19;UINT8 = 20;INT8 = 21; #if !defined(LITE_WITH_XPU) && !defined(LITE_WITH_HUAWEI_ASCEND_NPU) TestCast(place, abs_error, 20, 5); #endif TestCast(place, abs_error, 2, 5); #if defined(LITE_WITH_HUAWEI_ASCEND_NPU) TestCast(place, abs_error, 3, 5); TestCast(place, abs_error, 5, 3); #endif } } // namespace lite } // namespace paddle