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Diffstat (limited to 'compiler/locomotiv/src/Node/Softmax.cpp')
-rw-r--r-- | compiler/locomotiv/src/Node/Softmax.cpp | 122 |
1 files changed, 122 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/Softmax.cpp b/compiler/locomotiv/src/Node/Softmax.cpp new file mode 100644 index 000000000..352598b27 --- /dev/null +++ b/compiler/locomotiv/src/Node/Softmax.cpp @@ -0,0 +1,122 @@ +/* + * 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; + +#include <cassert> +#include <stdexcept> +#include <cmath> + +namespace +{ + +Index reduce_index(const Index &index, uint32_t axis) +{ + Index r_index; + + r_index.resize(index.rank()); + for (uint32_t i = 0; i < index.rank(); ++i) + r_index.at(i) = index.at(i); + r_index.at(axis) = 0; + + return r_index; +} + +Shape reduce_shape(const Shape &shape, uint32_t axis) +{ + Shape r_shape; + + r_shape.resize(shape.rank()); + for (uint32_t i = 0; i < shape.rank(); ++i) + r_shape.dim(i) = shape.dim(i); + r_shape.dim(axis) = 1; + + return r_shape; +} + +} // namespace + +namespace locomotiv +{ + +void NodeExecution::execute(loco::TensorSoftmax *softmax) +{ + auto input_data = annot_data(softmax->input()); + + validate(input_data, "Input not ready"); + validate(annot_domain(softmax->input()) == loco::Domain::Tensor, + "Input domain of TensorSoftmax is not Tensor"); + + std::unique_ptr<NodeData> softmax_data = nullptr; + + switch (input_data->dtype()) + { + case loco::DataType::FLOAT32: + { + auto axis = softmax->axis(); + + auto *input_shape = input_data->shape(); + auto input_bufptr = input_data->as_f32_bufptr(); + auto softmax_buf = make_buffer<float, LexicalLayout>(*input_data->shape()); + + auto reduce_sum_shape = reduce_shape(*input_shape, axis); + auto reduce_sum_bufptr = make_buffer<float, LexicalLayout>(reduce_sum_shape); + + for (IndexEnumerator e{*input_shape}; e.valid(); e.advance()) + { + const auto &index = e.current(); + const auto r_index = reduce_index(index, axis); + + reduce_sum_bufptr.at(r_index) += exp(input_bufptr->at(index)); + } + + for (IndexEnumerator e{*input_shape}; e.valid(); e.advance()) + { + const auto &index = e.current(); + const auto r_index = reduce_index(index, axis); + + softmax_buf.at(index) = exp(input_bufptr->at(index)) / reduce_sum_bufptr.at(r_index); + } + + softmax_data = make_data(softmax_buf); + break; + } + default: + throw std::runtime_error("NYI for this DataType"); + } + + assert(softmax_data != nullptr); + annot_data(softmax, std::move(softmax_data)); + annot_domain(softmax, annot_domain(softmax->input())); +} + +} // namespace locomotiv |