[Paddle-TRT] Add hard_sigmoid and hard_swish support(support MobilenetV3) (#23536)

* add hard_sigmoid trt op converter

* add hard_swish op converter and plugin. test=develop

paddle/fluid/inference/api/analysis_predictor.cc

@@ -942,6 +942,8 @@ USE_TRT_CONVERTER(batch_norm);
 USE_TRT_CONVERTER(concat);
 USE_TRT_CONVERTER(dropout);
 USE_TRT_CONVERTER(pad);
+USE_TRT_CONVERTER(hard_sigmoid);
+USE_TRT_CONVERTER(hard_swish);
 USE_TRT_CONVERTER(split);
 USE_TRT_CONVERTER(prelu);
 USE_TRT_CONVERTER(conv2d_transpose);

paddle/fluid/inference/tensorrt/convert/CMakeLists.txt

@@ -3,7 +3,7 @@ nv_library(tensorrt_converter
            SRCS mul_op.cc conv2d_op.cc fc_op.cc pool2d_op.cc elementwise_op.cc
                 batch_norm_op.cc activation_op.cc softmax_op.cc concat_op.cc dropout_op.cc
                 pad_op.cc split_op.cc prelu_op.cc leaky_relu_op.cc gelu_op.cc layer_norm_op.cc multihead_matmul_op.cc
-                shuffle_channel_op.cc swish_op.cc instance_norm_op.cc emb_eltwise_layernorm.cc skip_layernorm.cc
+                shuffle_channel_op.cc swish_op.cc instance_norm_op.cc emb_eltwise_layernorm.cc skip_layernorm.cc hard_sigmoid_op.cc hard_swish_op.cc
            DEPS tensorrt_engine tensorrt_plugin operator scope framework_proto op_registry)
 
 nv_test(test_op_converter SRCS test_op_converter.cc DEPS

paddle/fluid/inference/tensorrt/convert/hard_sigmoid_op.cc

+/* 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"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+
+/*
+ * HardSigmoidOp, IActivationLayer in TRT. This Layer doesn't has weights.
+ */
+class HardSigmoidOpConverter : public OpConverter {
+ public:
+  void operator()(const framework::proto::OpDesc& op,
+                  const framework::Scope& scope, bool test_mode) override {
+    VLOG(3) << "convert a fluid HardSigmoid op to tensorrt IActivationLayer "
+               "layer without bias";
+    framework::OpDesc op_desc(op, nullptr);
+    // Declare inputs
+    auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
+    float slope = boost::get<float>(op_desc.GetAttr("slope"));
+    float offset = boost::get<float>(op_desc.GetAttr("offset"));
+    auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Activation, *input,
+                                       nvinfer1::ActivationType::kHARD_SIGMOID);
+    layer->setAlpha(slope);
+    layer->setBeta(offset);
+
+    auto output_name = op_desc.Output("Out")[0];
+    RreplenishLayerAndOutput(layer, "hard_sigmoid", {output_name}, test_mode);
+  }
+};
+
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle
+
+REGISTER_TRT_OP_CONVERTER(hard_sigmoid, HardSigmoidOpConverter);

paddle/fluid/inference/tensorrt/convert/hard_swish_op.cc

+/* Copyright (c) 2020 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/hard_swish_op_plugin.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+
+/*
+ * HardSwish converter from fluid to tensorRT.
+ */
+class HardSwishOpConverter : public OpConverter {
+ public:
+  void operator()(const framework::proto::OpDesc& op,
+                  const framework::Scope& scope, bool test_mode) override {
+    VLOG(4) << "convert fluid HardSwish op to tensorrt HardSwish plugin";
+
+    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(
+            "HardSwish op has only 1 input, but got %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, 1,
+        platform::errors::InvalidArgument(
+            "HardSwish op has only 1 output, but got %d", output_num));
+
+    const float threshold =
+        op_desc.HasAttr("threshold")
+            ? boost::get<float>(op_desc.GetAttr("threshold"))
+            : 6.0f;
+    const float scale = op_desc.HasAttr("scale")
+                            ? boost::get<float>(op_desc.GetAttr("scale"))
+                            : 6.0f;
+    const float offset = op_desc.HasAttr("offset")
+                             ? boost::get<float>(op_desc.GetAttr("offset"))
+                             : 3.0f;
+
+    nvinfer1::ILayer* layer = nullptr;
+
+    plugin::HardSwishPlugin* plugin =
+        new plugin::HardSwishPlugin(threshold, scale, offset);
+    layer = engine_->AddPlugin(&input, input_num, plugin);
+
+    auto output_name = op_desc.Output("Out")[0];
+    RreplenishLayerAndOutput(layer, "hard_swish", {output_name}, test_mode);
+  }
+};
+
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle
+
+REGISTER_TRT_OP_CONVERTER(hard_swish, HardSwishOpConverter);

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -54,6 +54,8 @@ struct SimpleOpTypeSetTeller : public Teller {
       "relu",
       "softmax",
       "sigmoid",
+      "hard_sigmoid",
+      "hard_swish",
       "depthwise_conv2d",
       "batch_norm",
       "concat",

paddle/fluid/inference/tensorrt/plugin/CMakeLists.txt

@@ -3,5 +3,5 @@ nv_library(tensorrt_plugin
            prelu_op_plugin.cu  trt_plugin_factory.cc gelu_op_plugin.cu 
            pool_op_plugin.cu swish_op_plugin.cu layer_norm_op_plugin.cu
 instance_norm_op_plugin.cu emb_eltwise_layernorm_plugin.cu
-qkv_to_context_plugin.cu skip_layernorm_op_plugin.cu
+qkv_to_context_plugin.cu skip_layernorm_op_plugin.cu hard_swish_op_plugin.cu
            DEPS enforce tensorrt_engine prelu tensor bert_encoder_functor) 

paddle/fluid/inference/tensorrt/plugin/hard_swish_op_plugin.cu

+// Copyright (c) 2020 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 <cassert>
+#include <cstring>
+#include "paddle/fluid/inference/tensorrt/plugin/hard_swish_op_plugin.h"
+#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin_factory.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+namespace plugin {
+
+HardSwishPlugin* CreateHardSwishPluginDeserialize(const void* buffer,
+                                                  size_t length) {
+  return new HardSwishPlugin(buffer, length);
+}
+
+REGISTER_TRT_PLUGIN("hard_swish_plugin", CreateHardSwishPluginDeserialize);
+
+nvinfer1::Dims HardSwishPlugin::getOutputDimensions(
+    int index, const nvinfer1::Dims* in_dims, int nb_inputs) {
+  assert(nb_inputs == 1);
+  assert(index < this->getNbOutputs());
+  nvinfer1::Dims const& input_dims = in_dims[0];
+  nvinfer1::Dims output_dims = input_dims;
+  return output_dims;
+}
+
+template <typename T>
+__device__ T kMax(T a, T b) {
+  return a > b ? a : b;
+}
+
+template <typename T>
+__device__ T kMin(T a, T b) {
+  return a < b ? a : b;
+}
+
+template <typename T, unsigned TPB>
+__global__ void hard_swish_kernel(float threshold, float scale, float offset,
+                                  int n, const T* input, T* output) {
+  const int idx = blockIdx.x * TPB + threadIdx.x;
+  if (idx < n) {
+    const T in = input[idx];
+    output[idx] = in / scale * kMin<T>(kMax<T>(in + offset, 0), threshold);
+  }
+}
+
+int HardSwishPlugin::enqueue(int batch_size, const void* const* inputs,
+                             void** outputs, void*, cudaStream_t stream) {
+  const auto& input_dims = this->getInputDims(0);
+  int num = batch_size;
+  for (int i = 0; i < input_dims.nbDims; i++) {
+    num *= input_dims.d[i];
+  }
+  float threshold = threshold_;
+  float scale = scale_;
+  float offset = offset_;
+
+  const int block_size = 256;
+  const int grid_size = (num + block_size - 1) / block_size;
+
+  const float* input = static_cast<const float*>(inputs[0]);
+  float* output = static_cast<float*>(outputs[0]);
+  hard_swish_kernel<float, block_size><<<grid_size, block_size, 0, stream>>>(
+      threshold, scale, offset, num, input, output);
+
+  return cudaGetLastError() != cudaSuccess;
+}
+
+}  // namespace plugin
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/tensorrt/plugin/hard_swish_op_plugin.h

+// Copyright (c) 2019 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.
+
+#pragma once
+#include <stdio.h>
+#include <cassert>
+#include <string>
+#include <vector>
+#include "paddle/fluid/inference/tensorrt/engine.h"
+#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+namespace plugin {
+
+class HardSwishPlugin : public PluginTensorRT {
+ public:
+  HardSwishPlugin(const float threshold, const float scale, const float offset)
+      : threshold_(threshold), scale_(scale), offset_(offset) {}
+
+  // It was used for tensorrt deserialization.
+  // It should not be called by users.
+  HardSwishPlugin(void const* serialData, size_t serialLength) {
+    deserializeBase(serialData, serialLength);
+    DeserializeValue(&serialData, &serialLength, &threshold_);
+    DeserializeValue(&serialData, &serialLength, &scale_);
+    DeserializeValue(&serialData, &serialLength, &offset_);
+  }
+
+  ~HardSwishPlugin() {}
+  HardSwishPlugin* clone() const override {
+    return new HardSwishPlugin(threshold_, scale_, offset_);
+  }
+
+  const char* getPluginType() const override { return "hard_swish_plugin"; }
+  int getNbOutputs() const override { return 1; }
+  int initialize() override { return 0; }
+  nvinfer1::Dims getOutputDimensions(int index, const nvinfer1::Dims* inputs,
+                                     int nbInputDims) override;
+  int enqueue(int batchSize, const void* const* inputs, void** outputs,
+              void* workspace, cudaStream_t stream) override;
+
+ protected:
+  float threshold_;
+  float scale_;
+  float offset_;
+
+  size_t getSerializationSize() override {
+    return getBaseSerializationSize() + SerializedSize(threshold_) +
+           SerializedSize(scale_) + SerializedSize(offset_) +
+           SerializedSize(getPluginType());
+  }
+
+  // TRT will call this func  to serialize the configuration of TRT
+  // It should not be called by users.
+  void serialize(void* buffer) override {
+    SerializeValue(&buffer, getPluginType());
+    serializeBase(buffer);
+    SerializeValue(&buffer, threshold_);
+    SerializeValue(&buffer, scale_);
+    SerializeValue(&buffer, offset_);
+  }
+};
+
+}  // namespace plugin
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle