You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Paddle/paddle/fluid/inference/tensorrt/convert/swish_op.cc

85 lines
2.9 KiB

/* Copyright (c) 2018 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/swish_op_plugin.h"
namespace nvinfer1 {
class ILayer;
} // namespace nvinfer1
namespace paddle {
namespace framework {
class Scope;
namespace proto {
class OpDesc;
} // namespace proto
} // namespace framework
} // namespace paddle
namespace paddle {
namespace inference {
namespace tensorrt {
class SwishOpConverter : public OpConverter {
public:
void operator()(const framework::proto::OpDesc& op,
const framework::Scope& scope, bool test_mode) override {
VLOG(4) << "convert fluid swish op to tensorrt layer";
framework::OpDesc op_desc(op, nullptr);
// Declare inputs
int input_num = op_desc.Input("X").size();
PADDLE_ENFORCE_EQ(input_num, 1,
platform::errors::InvalidArgument(
"The input X's size must equal to 1 in TRT swish op."
" But received X's size %d.",
input_num));
auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
// Get output
size_t output_num = op_desc.Output("Out").size();
PADDLE_ENFORCE_EQ(
output_num, 1UL,
platform::errors::InvalidArgument(
"The ouput Out's size must equal to 1 in TRT swish op. "
"But received Out's size %u.",
output_num));
// Get attrs
float beta = BOOST_GET_CONST(float, op_desc.GetAttr("beta"));
nvinfer1::ILayer* layer = nullptr;
if (engine_->with_dynamic_shape()) {
#if IS_TRT_VERSION_GE(6000)
plugin::SwishPluginDynamic* plugin = new plugin::SwishPluginDynamic(beta);
layer = engine_->AddPluginV2(&input, input_num, 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 {
plugin::SwishPlugin* plugin = new plugin::SwishPlugin(beta);
layer = engine_->AddPlugin(&input, input_num, plugin);
}
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "swish", {output_name}, test_mode);
}
};
} // namespace tensorrt
} // namespace inference
} // namespace paddle
REGISTER_TRT_OP_CONVERTER(swish, SwishOpConverter);