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107 lines
4.1 KiB
107 lines
4.1 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 "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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#include "paddle/fluid/inference/tensorrt/plugin/slice_op_plugin.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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class SliceOpConverter : 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, bool test_mode) override {
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// This OP is implemented by trt dynamic shpae plugin.
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// Dynamic shape plugin requires TRT version greater than 6.0.
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VLOG(4) << "convert slice op to tensorrt layer";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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auto* input = engine_->GetITensor(op_desc.Input("Input")[0]);
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std::vector<int> axes =
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BOOST_GET_CONST(std::vector<int>, op_desc.GetAttr("axes"));
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std::vector<int> starts =
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BOOST_GET_CONST(std::vector<int>, op_desc.GetAttr("starts"));
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std::vector<int> ends =
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BOOST_GET_CONST(std::vector<int>, op_desc.GetAttr("ends"));
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PADDLE_ENFORCE_EQ(
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starts.size(), axes.size(),
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platform::errors::InvalidArgument(
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"The size of starts must be equal to the size of axes."));
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PADDLE_ENFORCE_EQ(
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ends.size(), axes.size(),
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platform::errors::InvalidArgument(
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"The size of ends must be equal to the size of axes."));
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auto input_dims = input->getDimensions();
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if (!engine_->with_dynamic_shape()) {
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// notice that input shape is [CHW] without batch axis when input has
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// static shape
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for (size_t i = input_dims.nbDims; i > 0; i--) {
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input_dims.d[i] = input_dims.d[i - 1];
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}
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input_dims.d[0] = 1; // fake batchsize, not useful here
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for (size_t i = 0; i < axes.size(); i++) {
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// split on batch is not supported in TensorRT
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PADDLE_ENFORCE_NE(axes[i], 0, platform::errors::InvalidArgument(
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"Invalid slice axis. Slice on batch "
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"axis is not supported in TensorRT"));
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if (starts[i] < 0) {
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starts[i] = std::max(starts[i] + input_dims.d[axes[i]], 0);
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}
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if (ends[i] < 0) {
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ends[i] = std::max(ends[i] + input_dims.d[axes[i]], 0);
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}
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ends[i] = std::min(ends[i], input_dims.d[axes[i]]);
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PADDLE_ENFORCE_GT(
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ends[i], starts[i],
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platform::errors::InvalidArgument(
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"Attr(ends) should be greater than attr(starts) in "
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"slice op. But received ends = %d, starts = %d.",
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ends[i], starts[i]));
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}
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}
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nvinfer1::ILayer* layer = nullptr;
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if (engine_->with_dynamic_shape()) {
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#if IS_TRT_VERSION_GE(6000)
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bool ban_fp16 = engine_->disable_trt_plugin_fp16();
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plugin::SlicePluginDynamic* plugin =
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new plugin::SlicePluginDynamic(starts, ends, axes, ban_fp16);
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layer = engine_->AddPluginV2(&input, 1, plugin);
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#else
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PADDLE_THROW(platform::errors::Fatal(
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"You are running the TRT Dynamic Shape mode, need to confirm that "
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"your TRT version is no less than 6.0"));
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#endif
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} else {
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bool ban_fp16 = engine_->disable_trt_plugin_fp16();
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plugin::SlicePlugin* plugin =
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new plugin::SlicePlugin(starts, ends, axes, ban_fp16);
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layer = engine_->AddPlugin(&input, 1, plugin);
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}
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auto output_name = op_desc.Output("Out")[0];
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RreplenishLayerAndOutput(layer, "slice", {output_name}, test_mode);
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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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REGISTER_TRT_OP_CONVERTER(slice, SliceOpConverter);
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