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108 lines
3.6 KiB
108 lines
3.6 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <gtest/gtest.h>
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#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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TEST(elementwise_op, add_weight) {
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std::unordered_set<std::string> parameters({"elementwise_add-Y"});
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framework::Scope scope;
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TRTConvertValidation validator(10, parameters, scope, 1 << 15);
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validator.DeclInputVar("elementwise_add-X", nvinfer1::DimsCHW(10, 3, 3));
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validator.DeclParamVar("elementwise_add-Y", nvinfer1::Dims3(10, 1, 1));
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validator.DeclOutputVar("elementwise_add-Out", nvinfer1::DimsCHW(10, 3, 3));
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// Prepare Op description
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framework::OpDesc desc;
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desc.SetType("elementwise_add");
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desc.SetInput("X", {"elementwise_add-X"});
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desc.SetInput("Y", {"elementwise_add-Y"});
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desc.SetOutput("Out", {"elementwise_add-Out"});
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int axis = 1;
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desc.SetAttr("axis", axis);
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validator.SetOp(*desc.Proto());
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validator.Execute(8);
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}
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TEST(elementwise_op, native) {
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for (std::string type : {"add", "mul"}) {
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int batch_size = 8;
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std::unordered_set<std::string> parameters;
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framework::Scope scope;
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TRTConvertValidation validator(batch_size, parameters, scope, 1 << 15);
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validator.DeclInputVar("elementwise_" + type + "-X",
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nvinfer1::DimsCHW(10, 3, 3));
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validator.DeclInputVar("elementwise_" + type + "-Y",
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nvinfer1::Dims3(10, 3, 3));
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validator.DeclOutputVar("elementwise_" + type + "-Out",
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nvinfer1::DimsCHW(10, 3, 3));
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// Prepare Op description
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framework::OpDesc desc;
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desc.SetType("elementwise_" + type);
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desc.SetInput("X", {"elementwise_" + type + "-X"});
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desc.SetInput("Y", {"elementwise_" + type + "-Y"});
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desc.SetOutput("Out", {"elementwise_" + type + "-Out"});
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int axis = -1;
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desc.SetAttr("axis", axis);
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validator.SetOp(*desc.Proto());
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validator.Execute(batch_size);
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}
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}
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TEST(elementwise_op, plugin) {
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for (std::string type : {"add", "mul"}) {
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int batch_size = 8;
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std::unordered_set<std::string> parameters;
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framework::Scope scope;
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TRTConvertValidation validator(batch_size, parameters, scope, 1 << 15);
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validator.DeclInputVar("elementwise_" + type + "-X",
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nvinfer1::DimsCHW(10, 3, 3));
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validator.DeclInputVar("elementwise_" + type + "-Y",
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nvinfer1::Dims3(10, 1, 1));
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validator.DeclOutputVar("elementwise_" + type + "-Out",
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nvinfer1::DimsCHW(10, 3, 3));
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// Prepare Op description
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framework::OpDesc desc;
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desc.SetType("elementwise_" + type);
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desc.SetInput("X", {"elementwise_" + type + "-X"});
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desc.SetInput("Y", {"elementwise_" + type + "-Y"});
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desc.SetOutput("Out", {"elementwise_" + type + "-Out"});
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int axis = -1;
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desc.SetAttr("axis", axis);
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validator.SetOp(*desc.Proto());
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validator.Execute(batch_size);
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}
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}
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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USE_OP(elementwise_add);
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USE_OP(elementwise_mul);
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