// This file is part of OpenCV project. // It is subject to the license terms in the LICENSE file found in the top-level directory // of this distribution and at http://opencv.org/license.html. #include #include #include "functors.hpp" #include "types.hpp" #include "vector_traits.hpp" #include "grid_stride_range.hpp" #include "execution.hpp" #include "../cuda4dnn/csl/stream.hpp" #include "../cuda4dnn/csl/span.hpp" using namespace cv::dnn::cuda4dnn::csl; using namespace cv::dnn::cuda4dnn::csl::device; namespace cv { namespace dnn { namespace cuda4dnn { namespace kernels { namespace raw { template __global__ void biasN_eltwise_op_generic_op_inplace_vec(Span inplace_output, size_type inner_size, View bias, View eltwise, const typename EltwiseOp::Params eltwise_params, const typename ActivationOp::Params act_params) { using vector_type = get_vector_type_t; auto inplace_output_vPtr = vector_type::get_pointer(inplace_output.data()); auto eltwise_vPtr = vector_type::get_pointer(eltwise.data()); EltwiseOp eltwise_op(eltwise_params); ActivationOp activation_op(act_params); for (auto i : grid_stride_range(inplace_output.size() / vector_type::size())) { const index_type bias_idx = (i / inner_size) % bias.size(); vector_type output_vec, eltwise_vec; v_load(output_vec, inplace_output_vPtr[i]); v_load(eltwise_vec, eltwise_vPtr[i]); for(int j = 0; j < output_vec.size(); j++) output_vec.data[j] = activation_op(eltwise_op(output_vec.data[j] + bias[bias_idx], eltwise_vec.data[j])); v_store(inplace_output_vPtr[i], output_vec); } } } template static void launch_vectorized_biasN_eltwise_op_generic_op_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise, const typename EltwiseOp::Params& eltwise_params, const typename ActivationOp::Params& act_params) { CV_Assert(is_fully_aligned(inplace_output, N)); CV_Assert(inplace_output.size() % bias.size() == 0); CV_Assert(is_fully_aligned(eltwise, N)); CV_Assert(inner_size % N == 0); auto kernel = raw::biasN_eltwise_op_generic_op_inplace_vec; auto policy = make_policy(kernel, inplace_output.size() / N, 0, stream); launch_kernel(kernel, policy, inplace_output, inner_size / N, bias, eltwise, eltwise_params, act_params); } template static void biasN_eltwise_op_generic_op_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise, const typename EltwiseOp::Params& eltwise_params = {}, const typename ActivationOp::Params& act_params = {}) { CV_Assert(inplace_output.size() == eltwise.size()); if (is_fully_aligned(inplace_output, 4) && is_fully_aligned(eltwise, 4) && inner_size % 4 == 0) { launch_vectorized_biasN_eltwise_op_generic_op_inplace(stream, inplace_output, inner_size, bias, eltwise, eltwise_params, act_params); } else if (is_fully_aligned(inplace_output, 2) && is_fully_aligned(eltwise, 2) && inner_size % 2 == 0) { launch_vectorized_biasN_eltwise_op_generic_op_inplace(stream, inplace_output, inner_size, bias, eltwise, eltwise_params, act_params); } else { launch_vectorized_biasN_eltwise_op_generic_op_inplace(stream, inplace_output, inner_size, bias, eltwise, eltwise_params, act_params); } } template void biasN_eltwise_sum_2_identity_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise) { biasN_eltwise_op_generic_op_inplace, IdentityFunctor>(stream, inplace_output, inner_size, bias, eltwise); } template void biasN_eltwise_sum_2_relu_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise, T slope) { biasN_eltwise_op_generic_op_inplace, ReLUFunctor>(stream, inplace_output, inner_size, bias, eltwise, {}, {slope}); } template void biasN_eltwise_sum_2_clipped_relu_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise, T floor, T ceiling) { CV_Assert(static_cast(floor) <= static_cast(ceiling)); biasN_eltwise_op_generic_op_inplace, ClippedReLUFunctor>(stream, inplace_output, inner_size, bias, eltwise, {}, {floor, ceiling}); } template void biasN_eltwise_sum_2_tanh_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise) { biasN_eltwise_op_generic_op_inplace, TanHFunctor>(stream, inplace_output, inner_size, bias, eltwise); } template void biasN_eltwise_sum_2_swish_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise) { biasN_eltwise_op_generic_op_inplace, SwishFunctor>(stream, inplace_output, inner_size, bias, eltwise); } template void biasN_eltwise_sum_2_mish_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise) { biasN_eltwise_op_generic_op_inplace, MishFunctor>(stream, inplace_output, inner_size, bias, eltwise); } template void biasN_eltwise_sum_2_sigmoid_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise) { biasN_eltwise_op_generic_op_inplace, SigmoidFunctor>(stream, inplace_output, inner_size, bias, eltwise); } template void biasN_eltwise_sum_2_power_inplace(const Stream& stream, Span inplace_output, std::size_t inner_size, View bias, View eltwise, T exp, T scale, T shift) { biasN_eltwise_op_generic_op_inplace, PowerFunctor>(stream, inplace_output, inner_size, bias, eltwise, {}, {exp, scale, shift}); } #if !defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 530) template void biasN_eltwise_sum_2_identity_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>); template void biasN_eltwise_sum_2_relu_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>, __half); template void biasN_eltwise_sum_2_clipped_relu_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>, __half, __half); template void biasN_eltwise_sum_2_tanh_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>); template void biasN_eltwise_sum_2_swish_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>); template void biasN_eltwise_sum_2_mish_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>); template void biasN_eltwise_sum_2_sigmoid_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>); template void biasN_eltwise_sum_2_power_inplace<__half>(const Stream&, Span<__half>, std::size_t, View<__half>, View<__half>, __half, __half, __half); #endif template void biasN_eltwise_sum_2_identity_inplace(const Stream&, Span, std::size_t, View, View); template void biasN_eltwise_sum_2_relu_inplace(const Stream&, Span, std::size_t, View, View, float); template void biasN_eltwise_sum_2_clipped_relu_inplace(const Stream&, Span, std::size_t, View, View, float, float); template void biasN_eltwise_sum_2_tanh_inplace(const Stream&, Span, std::size_t, View, View); template void biasN_eltwise_sum_2_swish_inplace(const Stream&, Span, std::size_t, View, View); template void biasN_eltwise_sum_2_mish_inplace(const Stream&, Span, std::size_t, View, View); template void biasN_eltwise_sum_2_sigmoid_inplace(const Stream&, Span, std::size_t, View, View); template void biasN_eltwise_sum_2_power_inplace(const Stream&, Span, std::size_t, View, View, float, float, float); }}}} /* namespace cv::dnn::cuda4dnn::kernels */