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Diffstat (limited to 'compiler/locomotiv/src/Node/TensorReduce.cpp')
-rw-r--r-- | compiler/locomotiv/src/Node/TensorReduce.cpp | 153 |
1 files changed, 153 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/TensorReduce.cpp b/compiler/locomotiv/src/Node/TensorReduce.cpp new file mode 100644 index 000000000..fae7a75c5 --- /dev/null +++ b/compiler/locomotiv/src/Node/TensorReduce.cpp @@ -0,0 +1,153 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. 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 "NodeExecution.h" +#include "NodeDataImpl.h" +#include "NodeDomain.h" +#include "Validation.h" + +#include <nncc/core/ADT/tensor/Shape.h> +#include <nncc/core/ADT/tensor/Buffer.h> +#include <nncc/core/ADT/tensor/Index.h> +#include <nncc/core/ADT/tensor/IndexEnumerator.h> +#include <nncc/core/ADT/tensor/LexicalLayout.h> + +using nncc::core::ADT::tensor::Index; +using nncc::core::ADT::tensor::IndexEnumerator; +using nncc::core::ADT::tensor::LexicalLayout; +using nncc::core::ADT::tensor::make_buffer; +using nncc::core::ADT::tensor::Shape; +using nncc::core::ADT::tensor::Buffer; + +#include <cassert> +#include <stdexcept> + +namespace +{ + +Index reduced_index(const Index &index, const loco::TensorAxisSet &axes) +{ + Index r_index; + + r_index.resize(index.rank()); + for (uint32_t i = 0; i < index.rank(); ++i) + r_index.at(i) = (axes.defined(i)) ? 0 : index.at(i); + + return r_index; +} + +Shape reduced_shape(const Shape &shape, const loco::TensorAxisSet &axes) +{ + Shape r_shape; + + r_shape.resize(shape.rank()); + for (uint32_t i = 0; i < shape.rank(); ++i) + r_shape.dim(i) = (axes.defined(i)) ? 1 : shape.dim(i); + + return r_shape; +} + +} // namespace + +namespace +{ + +template <typename T, loco::ReduceFunc F> struct ReduceFunction +{ + static void apply(Buffer<T> &lhs, const Buffer<T> &rhs, const loco::TensorAxisSet &axes) + { + throw std::runtime_error("Not supported ReduceFunc type"); + } +}; + +template <typename T> struct ReduceFunction<T, loco::ReduceFunc::Mean> +{ + static void apply(Buffer<T> &lhs, const Buffer<T> &rhs, const loco::TensorAxisSet &axes) + { + for (IndexEnumerator e{rhs.shape()}; e.valid(); e.advance()) + { + const auto &index = e.current(); + const auto r_index = reduced_index(index, axes); + + lhs.at(r_index) += rhs.at(index); + } + + uint32_t r_cnt = 1; + for (uint32_t i = 0; i < rhs.shape().rank(); ++i) + if (axes.defined(i)) + r_cnt *= rhs.shape().dim(i); + + for (IndexEnumerator e{lhs.shape()}; e.valid(); e.advance()) + { + const auto &index = e.current(); + lhs.at(index) /= static_cast<T>(r_cnt); + } + } +}; + +template <typename T> +void apply(Buffer<T> &lhs, const Buffer<T> &rhs, const loco::TensorReduce &node) +{ + switch (node.func()) + { + case loco::ReduceFunc::Mean: + ReduceFunction<T, loco::ReduceFunc::Mean>::apply(lhs, rhs, *node.axes()); + break; + + // TODO Support more ReduceFunc type + default: + break; + } +} + +} // namespace + +namespace locomotiv +{ + +void NodeExecution::execute(loco::TensorReduce *node) +{ + auto input_data = annot_data(node->input()); + auto input_shape = input_data->shape(); + + validate(input_data, "Input not ready"); + validate(annot_domain(node->input()) == loco::Domain::Tensor, + "Input domain of TensorReduce is not Tensor"); + + std::unique_ptr<NodeData> reduce_data = nullptr; + Shape r_shape = reduced_shape(*input_shape, *node->axes()); + switch (input_data->dtype()) + { + case loco::DataType::FLOAT32: + { + auto input_bufptr = input_data->as_f32_bufptr(); + auto reduce_buf = make_buffer<float, LexicalLayout>(r_shape); + + apply(reduce_buf, *input_bufptr, *node); + + reduce_data = make_data(reduce_buf); + break; + } + default: + throw std::runtime_error("NYI for this DataType"); + } + + assert(reduce_data != nullptr); + annot_data(node, std::move(reduce_data)); + annot_domain(node, annot_domain(node->input())); +} + +} // namespace locomotiv |