wehub-resource-sync
104 lines
3.6 KiB
C++
104 lines
3.6 KiB
C++
/* 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 "paddle/fluid/framework/data_layout.h"
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#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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namespace paddle::inference::tensorrt {
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class NearestInterpolateOpConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope,
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bool test_mode) override {
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VLOG(3) << "convert a nearest_interp op to tensorrt op";
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framework::OpDesc op_desc(op, nullptr);
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auto inputs = op_desc.Inputs();
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std::string input_name = op_desc.Input("X").front();
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std::string output_name = op_desc.Output("Out").front();
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auto input = engine_->GetITensor(input_name);
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auto data_layout = !op_desc.HasAttr("data_layout")
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? phi::DataLayout::NCHW
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: common::StringToDataLayout(PADDLE_GET_CONST(
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std::string, op_desc.GetAttr("data_layout")));
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auto interp_method =
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PADDLE_GET_CONST(std::string, op_desc.GetAttr("interp_method"));
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bool align_corners =
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PADDLE_GET_CONST(bool, op_desc.GetAttr("align_corners"));
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auto input_names = op_desc.Input("X");
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auto scale = PADDLE_GET_CONST(float, op_desc.GetAttr("scale"));
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auto out_h = PADDLE_GET_CONST(int, op_desc.GetAttr("out_h"));
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auto out_w = PADDLE_GET_CONST(int, op_desc.GetAttr("out_w"));
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auto layer = TRT_ENGINE_ADD_LAYER(engine_, Resize, *input);
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#if IS_TRT_VERSION_GE(8600)
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if (align_corners) {
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layer->setCoordinateTransformation(
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nvinfer1::ResizeCoordinateTransformation::kALIGN_CORNERS);
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}
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#else
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layer->setAlignCorners(align_corners);
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#endif
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auto in_dim = input->getDimensions();
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float scale_h = 1.f;
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float scale_w = 1.f;
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std::vector<float> scales;
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if (scale > 0.f) {
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scale_h = scale;
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scale_w = scale;
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} else {
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// axis are different in static/dynamic mode
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bool with_dynamic = true;
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if (!with_dynamic) {
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int h_axis = (data_layout == phi::DataLayout::NCHW) + with_dynamic;
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int w_axis = (data_layout == phi::DataLayout::NCHW) + 1 + with_dynamic;
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scale_h =
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static_cast<float>(out_h) / static_cast<float>(in_dim.d[h_axis]);
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scale_w =
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static_cast<float>(out_w) / static_cast<float>(in_dim.d[w_axis]);
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}
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}
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scales.push_back(1.f);
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if (data_layout == phi::DataLayout::NCHW) {
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scales.push_back(1.f);
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scales.push_back(scale_h);
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scales.push_back(scale_w);
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} else if (data_layout == phi::DataLayout::NHWC) {
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// NHWC
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scales.push_back(scale_h);
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scales.push_back(scale_w);
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scales.push_back(1.f);
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} else {
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PADDLE_THROW(
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common::errors::InvalidArgument("Data layout must be NCHW or NHWC."));
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}
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layer->setScales(scales.data(), scales.size());
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ReplenishLayerAndOutput(layer, "nearest_interp", {output_name}, test_mode);
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(nearest_interp, NearestInterpolateOpConverter);
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