wehub-resource-sync
96 lines
3.2 KiB
C++
96 lines
3.2 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 <algorithm>
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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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/*
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* SoftMaxOp, ISoftMaxLayer in TRT. This Layer doesn't has weights.
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*/
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class SoftMaxOpConverter : 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 softmax op to tensorrt softmax layer without bias";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]);
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nvinfer1::Dims input_shape = input1->getDimensions();
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int input_dims = input_shape.nbDims;
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int axis = op_desc.HasAttr("axis")
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? PADDLE_GET_CONST(int, op_desc.GetAttr("axis"))
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: -1;
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// support 0 or 1 dims input
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bool is_0_dims = input_dims == 0;
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bool is_1_dims = input_dims == 1;
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if (is_0_dims || is_1_dims) {
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auto reshaped_layer = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input1);
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nvinfer1::Dims reshaped_dims;
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reshaped_dims.nbDims = 2;
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reshaped_dims.d[0] = 1;
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reshaped_dims.d[1] = is_0_dims ? 1 : input_shape.d[0];
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reshaped_layer->setReshapeDimensions(reshaped_dims);
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input1 = reshaped_layer->getOutput(0);
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input_shape = input1->getDimensions();
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input_dims = input_shape.nbDims;
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axis = -1;
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}
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auto* layer = TRT_ENGINE_ADD_LAYER(engine_, SoftMax, *input1);
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uint32_t axes = std::max(0, input_dims - 3);
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// TODO(cryoco): Poor workaround. Fix padded dims problem when TRT layers
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// support Nd.
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// Tips: Dynamic shape already fixes.
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int padded_dims = 0;
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int explicit_batch = 1;
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for (int i = input_dims - 1; i > explicit_batch; i--) {
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if (input_shape.d[i] == 1) {
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padded_dims += 1;
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} else {
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break;
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}
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}
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if (axis < 0) {
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axes = input_dims + axis;
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} else {
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axes = axis;
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}
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layer->setAxes(1 << axes);
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auto output_name = op_desc.Output("Out")[0];
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// support 0 or 1 dims input
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if (is_0_dims || is_1_dims) {
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auto reshaped_layer =
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TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *layer->getOutput(0));
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reshaped_layer->setReshapeDimensions(
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engine_->GetITensor(op_desc.Input("X")[0])->getDimensions());
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ReplenishLayerAndOutput(
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reshaped_layer, "reshape_softmax_reshape", {output_name}, test_mode);
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} else {
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ReplenishLayerAndOutput(layer, "softmax", {output_name}, test_mode);
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}
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}
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};
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} // namespace paddle::inference::tensorrt
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USE_OP_ITSELF(softmax);
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REGISTER_TRT_OP_CONVERTER(softmax, SoftMaxOpConverter);
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