// 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. #include "lite/kernels/arm/pool_compute.h" #include #include #include "lite/backends/arm/math/funcs.h" #include "lite/core/op_registry.h" #include "lite/core/type_system.h" namespace paddle { namespace lite { namespace kernels { namespace arm { void PoolCompute::PrepareForRun() { auto& ctx = this->ctx_->template As(); } void PoolCompute::Run() { auto& param = Param(); auto& in_dims = param.x->dims(); auto& out_dims = param.output->dims(); const float* din = param.x->data(); float* dout = param.output->mutable_data(); std::vector& ksize = param.ksize; std::vector& strides = param.strides; std::vector& paddings = param.paddings; std::string& pooling_type = param.pooling_type; bool global_pooling = param.global_pooling; bool exclusive = param.exclusive; bool adaptive = param.adaptive; bool ceil_mode = param.ceil_mode; bool use_quantizer = param.use_quantizer; std::string& data_format = param.data_format; bool kps_equal = (ksize[0] == ksize[1]) && (strides[0] == strides[1]) && (paddings[0] == paddings[1]); if (global_pooling) { for (size_t i = 0; i < ksize.size(); ++i) { paddings[i] = 0; ksize[i] = static_cast(in_dims[i + 2]); } if (pooling_type == "max") { lite::arm::math::pooling_global_max(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "invoking pooling_global_max"; return; } else if (pooling_type == "avg") { lite::arm::math::pooling_global_avg(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "invoking pooling_global_ave"; return; } } else { if (ksize[0] == 2 && strides[0] == 2 && paddings[0] == 0 && kps_equal) { if (pooling_type == "max") { lite::arm::math::pooling2x2s2_max(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "invoking pooling2x2s2_max"; return; } else if (pooling_type == "avg") { lite::arm::math::pooling2x2s2_avg(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3], exclusive); VLOG(3) << "invoking pooling2x2s2_avg"; return; } } else if (ksize[0] == 3 && strides[0] == 1 && paddings[0] == 1 && kps_equal) { if (pooling_type == "max") { lite::arm::math::pooling3x3s1p1_max(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "invokingpooling3x3s1p1_max"; return; } else if (pooling_type == "avg") { lite::arm::math::pooling3x3s1p1_avg(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3], exclusive); VLOG(3) << "invoking pooling3x3s1p1_avg"; return; } } else if (ksize[0] == 3 && strides[0] == 2 && paddings[0] == 0 && kps_equal) { if (pooling_type == "max") { lite::arm::math::pooling3x3s2p0_max(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "pooling3x3s2p0_max"; return; } else if (pooling_type == "avg") { lite::arm::math::pooling3x3s2p0_avg(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3], exclusive); VLOG(3) << "invoking pooling3x3s2p0_avg"; return; } } else if (ksize[0] == 3 && strides[0] == 2 && paddings[0] == 1 && kps_equal) { if (pooling_type == "max") { lite::arm::math::pooling3x3s2p1_max(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3]); VLOG(3) << "invoking pooling3x3s2p1_max"; return; } else if (pooling_type == "avg") { lite::arm::math::pooling3x3s2p1_avg(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3], exclusive); VLOG(3) << "invoking pooling3x3s2p1_avg"; return; } } } lite::arm::math::pooling_basic(din, dout, out_dims[0], out_dims[1], out_dims[2], out_dims[3], in_dims[1], in_dims[2], in_dims[3], ksize, strides, paddings, global_pooling, exclusive, adaptive, ceil_mode, use_quantizer, pooling_type); VLOG(3) << "invoking pooling_basic"; } } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( pool2d, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::PoolCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize();