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2 changes: 2 additions & 0 deletions paddle/fluid/inference/api/analysis_predictor.cc
Original file line number Diff line number Diff line change
Expand Up @@ -1198,6 +1198,8 @@ USE_TRT_CONVERTER(affine_channel);
USE_TRT_CONVERTER(multiclass_nms);
USE_TRT_CONVERTER(nearest_interp);
USE_TRT_CONVERTER(reshape);
USE_TRT_CONVERTER(reduce_sum);
USE_TRT_CONVERTER(gather_nd);
#endif

namespace paddle_infer {
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2 changes: 2 additions & 0 deletions paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,8 @@ nv_library(tensorrt_converter
multiclass_nms_op.cc
nearest_interp_op.cc
reshape_op.cc
reduce_op.cc
gather_nd_op.cc
DEPS tensorrt_engine tensorrt_plugin operator scope framework_proto op_registry)

nv_test(test_op_converter SRCS test_op_converter.cc DEPS
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17 changes: 13 additions & 4 deletions paddle/fluid/inference/tensorrt/convert/emb_eltwise_layernorm.cc
Original file line number Diff line number Diff line change
Expand Up @@ -40,10 +40,19 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
auto word_emb_name = op_desc.Input("WordEmbedding").front();
auto pos_emb_name = op_desc.Input("PosEmbedding").front();
auto sent_emb_name = op_desc.Input("SentEmbedding").front();
std::vector<std::string> id_names = {word_id_name, pos_id_name,
sent_id_name};
std::vector<std::string> emb_names = {word_emb_name, pos_emb_name,
sent_emb_name};

std::vector<std::string> id_names;
std::vector<std::string> emb_names;

if (engine_->use_oss()) {
id_names =
std::vector<std::string>{word_id_name, pos_id_name, sent_id_name};
emb_names =
std::vector<std::string>{word_emb_name, pos_emb_name, sent_emb_name};
} else {
id_names = op_desc.Input("Ids");
emb_names = op_desc.Input("Embs");
}

int input_num = id_names.size();

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70 changes: 70 additions & 0 deletions paddle/fluid/inference/tensorrt/convert/gather_nd_op.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,70 @@
/* Copyright (c) 2021 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 "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/plugin/gather_nd_op_plugin.h"

namespace paddle {
namespace inference {
namespace tensorrt {

class GatherNdOpConverter : public OpConverter {
public:
void operator()(const framework::proto::OpDesc& op,
const framework::Scope& scope, bool test_mode) override {
VLOG(4) << "convert a paddle gather_nd op to tensorrt gather_nd plugin";
framework::OpDesc op_desc(op, nullptr);

// Declare inputs
std::vector<nvinfer1::ITensor*> inputs;
auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
auto* index = engine_->GetITensor(op_desc.Input("Index")[0]);
inputs.emplace_back(input);
inputs.emplace_back(index);

nvinfer1::ILayer* layer = nullptr;
if (engine_->with_dynamic_shape()) {
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我看在op_teller里已经有这个判断了,这里是不是不用再加了

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done

#if IS_TRT_VERSION_GE(6000)
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现在可以不加这个检查了,我们不支持TRT6以下版本了

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done

bool with_fp16 =
engine_->WithFp16() && !engine_->disable_trt_plugin_fp16();
plugin::GatherNdPluginDynamic* plugin =
new plugin::GatherNdPluginDynamic(with_fp16);
layer = engine_->AddDynamicPlugin(inputs.data(), inputs.size(), plugin);
#else
PADDLE_THROW(platform::errors::Fatal(
"You are running the TRT Dynamic Shape mode, need to confirm that "
"your TRT version is no less than 6.0"));
#endif
} else {
PADDLE_THROW(platform::errors::Fatal(
"gather_nd plugin only support dynamic mode."));
}

std::string layer_name = "gather_nd (Output: ";
auto output_name = op_desc.Output("Out")[0];
layer->getOutput(0)->setName(output_name.c_str());
engine_->SetITensor(output_name, layer->getOutput(0));
layer_name += output_name;
if (test_mode) {
engine_->DeclareOutput(output_name);
}
layer->setName((layer_name + ")").c_str());
}
};

} // namespace tensorrt
} // namespace inference
} // namespace paddle

REGISTER_TRT_OP_CONVERTER(gather_nd, GatherNdOpConverter);
90 changes: 90 additions & 0 deletions paddle/fluid/inference/tensorrt/convert/reduce_op.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,90 @@
/* Copyright (c) 2021 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 <NvInfer.h>
#include <sys/types.h>

#include <cstddef>
#include <cstdint>
#include <vector>

#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"

namespace paddle {
namespace framework {
class Scope;

namespace proto {
class OpDesc;
} // namespace proto
} // namespace framework
} // namespace paddle

namespace paddle {
namespace inference {
namespace tensorrt {

class ReduceSumOpConverter : public OpConverter {
public:
void operator()(const framework::proto::OpDesc& op,
const framework::Scope& scope, bool test_mode) override {
VLOG(4) << "convert a paddle reduce_sum op to tensorrt reduce layer";
framework::OpDesc op_desc(op, nullptr);

auto* x = engine_->GetITensor(op_desc.Input("X").front());
nvinfer1::Dims input_shape = x->getDimensions();
int input_dims = input_shape.nbDims;

bool keep_dim = BOOST_GET_CONST(bool, op_desc.GetAttr("keep_dim"));
std::vector<int32_t> dim =
BOOST_GET_CONST(std::vector<int32_t>, op_desc.GetAttr("dim"));
bool reduce_all = BOOST_GET_CONST(bool, op_desc.GetAttr("reduce_all"));
Comment on lines +49 to +52
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这些属性可以在op_teller里判断是否有,没有的话就不转TRT了

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done


// Now we only support dynamic_shape mode.
nvinfer1::IReduceLayer* layer = nullptr;
if (reduce_all) {
uint32_t reduce_dim = 0;
for (int i = 0; i < input_dims; ++i) {
reduce_dim |= 1 << i;
}
layer = TRT_ENGINE_ADD_LAYER(engine_, Reduce, *x,
nvinfer1::ReduceOperation::kSUM, reduce_dim,
keep_dim);
} else {
auto CvtToBitMask = [&](const std::vector<int32_t>& dims) -> uint32_t {
uint32_t res = 0;
for (auto x : dims) {
if (x < 0) {
res |= 1 << (x + input_dims);
} else {
res |= 1 << x;
}
}
return res;
};
layer = TRT_ENGINE_ADD_LAYER(engine_, Reduce, *x,
nvinfer1::ReduceOperation::kSUM,
CvtToBitMask(dim), keep_dim);
}

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "reduce_sum", {output_name}, test_mode);
}
};

} // namespace tensorrt
} // namespace inference
} // namespace paddle

REGISTER_TRT_OP_CONVERTER(reduce_sum, ReduceSumOpConverter);
2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/reshape_op.cc
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ class ReshapeOpConverter : public OpConverter {
framework::OpDesc op_desc(op, nullptr);
// Declare inputs
auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
const std::vector<int>& shape =
std::vector<int> shape =
BOOST_GET_CONST(std::vector<int>, op_desc.GetAttr("shape"));
int nbDims_num = shape.size();
nvinfer1::Dims reshape_dim;
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35 changes: 35 additions & 0 deletions paddle/fluid/inference/tensorrt/op_teller.cc
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
// limitations under the License.

#include "paddle/fluid/inference/tensorrt/op_teller.h"

#include "paddle/fluid/framework/block_desc.h"
#include "paddle/fluid/framework/data_layout.h"

Expand Down Expand Up @@ -122,11 +123,13 @@ struct SimpleOpTypeSetTeller : public Teller {
"flatten2",
"flatten",
"gather",
"gather_nd",
"yolo_box",
"roi_align",
"affine_channel",
"nearest_interp",
"anchor_generator",
"reduce_sum",
};
};

Expand Down Expand Up @@ -324,6 +327,30 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
if (!with_dynamic_shape || desc.Input("Axis").size() > 0) return false;
}

if (op_type == "gather_nd") {
auto* block = desc.Block();
auto x_var_name = desc.Input("X")[0];
auto index_var_name = desc.Input("Index")[0];
auto* x_var_desc = block->FindVar(x_var_name);
auto* index_var_desc = block->FindVar(index_var_name);

// The index input must be int32 datatype.
if (index_var_desc->GetDataType() !=
paddle::framework::proto::VarType_Type::VarType_Type_INT32) {
VLOG(3) << "gather_nd op Index input data type must be int32";
return false;
}

const auto index_shape = index_var_desc->GetShape();
const auto x_shape = x_var_desc->GetShape();
if (x_shape.size() != index_shape.size()) {
VLOG(3) << "gather_nd op Index input dims size [" << index_shape.size()
<< " ] not equal to x dims size [" << x_shape.size() << "]";
return false;
}
if (!with_dynamic_shape) return false;
}

if (op_type == "yolo_box") {
if (with_dynamic_shape) return false;
bool has_attrs =
Expand Down Expand Up @@ -684,6 +711,14 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
if (shape.size() >= nvinfer1::Dims::MAX_DIMS) return false;
}
}

if (op_type == "reduce_sum") {
if (!with_dynamic_shape) {
VLOG(3) << "the reduce_sum does not support static shape yet";
return false;
}
}

if ((*teller)(op_type, desc, use_no_calib_int8)) return true;
}
return false;
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1 change: 1 addition & 0 deletions paddle/fluid/inference/tensorrt/plugin/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@ nv_library(tensorrt_plugin
anchor_generator_op_plugin.cu
yolo_box_op_plugin.cu
roi_align_op_plugin.cu
gather_nd_op_plugin.cu
DEPS enforce tensorrt_engine prelu tensor bert_encoder_functor)

nv_test(test_split_plugin SRCS test_split_plugin.cc DEPS
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